{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0d70bef3",
   "metadata": {},
   "source": [
    "# Introduction to crisscross: Extracting spectra from crowded regions\n",
    "This notebook shows how to extract HETG spectra from a crowded region by running crisscross to handle confusion in two end-to-end examples:\n",
    "\n",
    "1.  covers a single ObsID in depth and \n",
    "2.  demonstrates how to run crisscross on multiple ObsIDs and combine the resulting spectra. \n",
    "\n",
    "More information and examples on `crisscross` and its helper function `clean_spec` can be found on their respective ahelp pages (e.g., type [\"ahelp crisscross\"](https://cxc.cfa.harvard.edu/ciao/ahelp/crisscross.html) and [\"ahelp clean_spec\"](https://cxc.cfa.harvard.edu/ciao/ahelp/clean_spec.html) on the command line in CIAO)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8370afc0",
   "metadata": {},
   "source": [
    "## Crisscross Summary\n",
    "`crisscross` and its helper tool `clean_spec` allow users to analyze Chandra High Energy Transmission Grating (HETG) \n",
    "spectra that are extracted from a field of view with multiple astrophysical X-ray sources. The HETG \n",
    "instrument will disperse events onto the ACIS CCDs from all sources in the field of view. If there are several \n",
    "sufficiently-bright X-ray sources then there is a potential for 'confusion' to occur. Confusion is a term used \n",
    "here for scenarios where [standard HETG spectral extractions](https://cxc.harvard.edu/ciao/threads/gspec.html) of a source may erroneously assign events (counts) from a different astrophysical source to the extracted spectrum. This can result in events from an unrelated astrophysical source 'confusing' the spectrum of an extracted source.\n",
    "\n",
    "crisscross is used to identify when spectral confusion occurs for a list of input sources (or a single source) \n",
    "and generates 'confusion tables' which identify the wavelengths in each source's spectrum that are likely to \n",
    "include X-ray events from unrelated field astrophysical sources. The user can then choose to remove all events \n",
    "from the source spectrum in the wavelength range where this confusion occurs. The helper program \n",
    "`clean_spec` uses the `crisscross` output confusion tables and input HETG PHA spectra to generate 'cleaned' spectra \n",
    "(and ARFs) where these events are removed. crisscross is intended for crowded X-ray fields with multiple \n",
    "observations such as stellar clusters."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42a60073",
   "metadata": {},
   "source": [
    "## Running crisscross\n",
    "\n",
    "First, packages and tools used later in the notebook have to be imported."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "649d0261",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import glob\n",
    "import shutil\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from ciao_contrib.runtool import *\n",
    "from ciao_contrib.cda.data import download_chandra_obsids\n",
    "from sherpa.astro.ui import *\n",
    "from sherpa_contrib.load_hetg_resp import load_gratings_pha2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f32d464",
   "metadata": {},
   "source": [
    "## (1) Run crisscross for a single source on a single ObsID"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07051d55",
   "metadata": {},
   "source": [
    "This example uses ObsID 3, a crowded HETG observation of a pre-main sequence stellar cluster.\n",
    "The data is downloaded with the `download_chandra_obsid` script. A return value of \"True\" means that the download was successful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b2e84ee7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[True]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "download_chandra_obsids([3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8795a368",
   "metadata": {},
   "source": [
    "The code below will extract the spectrum of a single source in the field of view using `chandra_repro` and the source coordinates. COUP 394 is a young, pre-main sequence star whose X-ray emission is generated by a hot corona. The commands below will produce only responses for the +1/-1 HEG/MEG orders. Users that wish to generate responses for more orders should use the 'tg_orders' parameter with `chandra_repro`. \n",
    "\n",
    "Users that wish to see spectra from other sources in the field of view can modify the variables below before running the remaining cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c96620ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "src_RA = 83.79475306\n",
    "src_DEC = -5.39575306\n",
    "obsid = 3\n",
    "src_root = 'COUP_394'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8fd90c7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters for chandra_repro:\n",
      "\n",
      "Required parameters:\n",
      "               indir = 3                Input directory\n",
      "              outdir =                  Output directory (default = $indir/repro)\n",
      "\n",
      "Optional parameters:\n",
      "                root = COUP_394         Root for output filenames\n",
      "            badpixel = True             Create a new bad pixel file?\n",
      "      process_events = True             Create a new level=2 event file?\n",
      "            destreak = True             Destreak the ACIS-8 chip?\n",
      "          set_ardlib = True             Set ardlib.par with the bad pixel file?\n",
      "        check_vf_pha = False            Clean ACIS background in VFAINT data?\n",
      "             pix_adj = default          Pixel randomization: default|edser|none|randomize\n",
      "      tg_zo_position = 83.79475306,-5.39575306  Method to determine gratings 0th order location: evt2|detect|R.A. & Dec.\n",
      "           tg_orders = default          List of orders to extract: none, default, or comma separated list\n",
      "         asol_update = True             If necessary, apply boresight correction to aspect solution file?\n",
      "           pi_filter = True             Apply PI background filter to HRC-S+LETG data?\n",
      "       patch_hrc_ssc = False            Patch HRC Secondary Science Corruption?\n",
      "             cleanup = True             Cleanup intermediate files on exit\n",
      "             clobber = False            Clobber existing file\n",
      "             verbose = 1                Debug Level(0-5)\n"
     ]
    }
   ],
   "source": [
    "# run chandra_repro using the zeroth order source location for COUP 394\n",
    "\n",
    "chandra_repro.punlearn()\n",
    "chandra_repro.indir = obsid\n",
    "chandra_repro.root = src_root\n",
    "chandra_repro.tg_zo_position = f'{src_RA},{src_DEC}'\n",
    "chandra_repro.clobber=False\n",
    "\n",
    "print(chandra_repro)\n",
    "\n",
    "a = chandra_repro()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f633aa9",
   "metadata": {},
   "source": [
    "Lets take a look at the source's spectra using Sherpa. We can use the sherpa-contrib function `load_gratings_pha2` to identify and load the pipeline response files (ARFs and RMFs) whose names are in the PHA2 spectrum header. Since the PHA2 file contains all spectra for 12 orders (-3, -2, -1, +1, +2, +3 for HEG and MEG each), sherpa data ids 1-12 will be used. If the directory does not include all 12 HETG responses then only those identified will be loaded; this causes the warning messages below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4d7b0e24",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "WARNING-- The identified number of ARFs [4] does not match the number of PHA spectra [12] in the PHA2 file. Only the responses found will be included.\n",
      "\n",
      "\n",
      "WARNING-- The identified number of RMFs [4] does not match the number of PHA spectra [12] in the PHA2 file. Only the responses found will be included.\n",
      "\n",
      "read background_up into a dataset from file 3/repro/COUP_394_repro_pha2.fits\n",
      "read background_down into a dataset from file 3/repro/COUP_394_repro_pha2.fits\n",
      "Multiple data sets have been input: 1-12\n"
     ]
    }
   ],
   "source": [
    "clean() #run clean to clean out all datasets and model definitions in Sherpa to start fresh \n",
    "\n",
    "original_pha2 = f'{obsid}/repro/{src_root}_repro_pha2.fits'\n",
    "load_gratings_pha2(pha2_file=original_pha2, use_errors=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9d5ac64",
   "metadata": {},
   "source": [
    "Now that the data are loaded, Sherpa can plot the brightest orders (HEG-1, HEG+1, MEG-1, MEG+1). Since there is not much data past 20 Å for this source, the plot limits the X-axis range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "63589fae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataset 3: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 4: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 9: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 10: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 3: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 4: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 9: 1:41.96 Wavelength (Angstrom) (unchanged)\n",
      "dataset 10: 1:41.96 Wavelength (Angstrom) (unchanged)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 900x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Spectral orders in the PHA2 files are heg-3, heg-2, heg-1, heg+1, heg+2, heg+3, meg-3, meg-2, meg-1, meg+1, meg+2, meg+3\n",
    "# Python starts counting at 0, so indices [3,4,9,10] select (heg -1/+1 and meg-1/+1)\n",
    "spec_ids = [3,4,9,10]\n",
    "\n",
    "# Each id must be set to the 'wave' analysis to plot in angstrom (instead of keV)\n",
    "for i in spec_ids:\n",
    "    set_analysis(i, 'wave')\n",
    "\n",
    "bin_num=3\n",
    "for i in spec_ids:\n",
    "    group_width(i, bin_num)\n",
    "\n",
    "# Create an arm label for the subplot names\n",
    "arm_label = ['heg-1','heg+1','meg-1','meg+1']\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "plot(\"data\", 3, \"data\", 4, \"data\", 9, \"data\", 10, \n",
    "     yerrorbars=False, color='red', linestyle='-', marker=None)\n",
    "\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)\n",
    "axes = plt.gcf().axes\n",
    "\n",
    "# set the same x-limits for all panels:\n",
    "for ax, arm in zip(axes, arm_label):\n",
    "    ax.set_xlim(0, 20)\n",
    "    ax.set_title(arm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f39a354b",
   "metadata": {},
   "source": [
    "Similarly, the spectral response for the source can be plotted using the ARF files. This shows the sensitivity of the detector at the extracted spectral location."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0c6c97a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xp0KFCvENi5VlE9Cjhz7/9VcR2/pSIopujgoCueCdUuTYMVcQmD69SJMm+vqyZSLnzvHgElFUKFWqlGzYsEFNAe3UqZO0a9dOtm7dGnd/KmR+tME0Uc/b7Hr37i2nTp2KOx04cCCo+09hdPWqPq9Y0XVbmTKujNrdu7u2IaKo5qggkAveKUVQGgIuXtTnb7zhuu+rr3hwiSgqpEuXTm699VapXLmyGsWrWLGi/O9//1NJYMBz1O/o0aPxRgftMKJoso2aE0X5SODtt7tuS51a5L33RDJnFvnjD/TIh233iChGg0AueKcUKVDAvZFLm1akfXt9memviShKYaQP6/qKFSumAsEFCxbE3Xf58mVZunSp1KhRI6z7SA5hRvn+6zBQLAtzhkX69NHX+/cXYTZZoqjnqCAwGAvegYveYwQaMsif33XbW2/p6aEbN4p8/nnYdo2IKBBee+01WbZsmezdu1etDUQm0CVLlkjr1q3VlM+uXbvKwIED1TrBzZs3S/v27SVTpkzSqlUrvgEksnmzPgq5c7uOxoULrqmgaD+PHxcZO5ZHiyjKpY72Be/ARe8xxr72pWBBkU6d9OX/+z+RU6fCtltERCl15MgRadu2rVoXeP/998uqVatk7ty5qhYg9OjRQwWCnTt3VtNFDx48KPPnz5csWbLw4JOImep7/rzraJj6gFhLj0AQunVzdawSUVRKHe0L3oGL3mOErwbr3Xf1VNGjR13TXYiIItDYsWPVKCBmuGCt38KFC+MCQEB72L9/fzl06JBcvHhRTQVFvUAiJVMmfW7PAGtPBGOWUMAvv/CgEUWx1NG+4B246D3GeHYKYLH7xx/ry8OHu6bDEBERxZLr112jfoZ9/V+OHCLVq+vLzz8f4p0jopgOAj1xwTsl4cOiz72NDDdrpovIY5uBA3lQiYgodttJZAT1nA5qDBqkz7dtEzl9OoQ7R0QxGwRywTulSGLrF958U59PnSqycycPNhERxeZIoL2z1Nxm1Krluvz66yHaMSIKtTTiwAXvWMuQLVs2qVChQrwF7xcuXFAL3k+cOCFVq1blgneKz9ca0Zo1XZdXrRIpUYJHj4iIYnsk0DMIRBt6000iJ0+K/P57aPePiGIzCMSC94SYBe84EcXjTyaz227TU1xMQXkiIqJY4c9IIMydK1KtmsjSpSLLloncc0/o9pGIYm86KFFAJJQtFkGgtzUQRERE0c7bSKC30klVq4o89pi+/OCDInPmhGgHiShUGARSbI0Epk0bPyW2P4978GDy94uIiMipCdTs5SLsPv1UpHRpXVOwUSORy5dDs49EFBIMAim2RgLT/DcDOikZzxo21EXnx49P+b4RERGFi5n6iZFA1NCtXFnkhRe8b5s7t8jata7rX38dmn0kopBgEEixUSLCMD2Z+/b5/7hYGwFPP+3faCMREZHT28mePUVWrxbJmjXx4vIweXLw94+IQoZBIMWWs2f1eZ48ujF86CGR7NlFzp3z7++//DKou0dERBSSkUB/NWmiz3/8MTj7RERhwSCQYmsksGRJV0OIKaGzZ4ucOCHy3nu+/6ZiRdflAQO8Z1IjIiKKhnbSU5s2rsvMrE0UNRgEUvTwZ6qm6f1EIHftmuv2ceN8/429ThLKS0yYkJK9JCIiiryRQBg5MvD7RERhwSCQok9CPZzmPs8gMKHsnzlz6vPatfX5m28ySxoREUWeI0eSPhKIrNpme5aKIIoaDAIptqa5mN7PwYNF7r3X/b5DhxJ+XGRSy5ZNZP9+kWnTArLLREREIWPauaTWykX7BwsWiEyfHv/+rVt1Bm0ulyCKGAwCKbbYp8Bs2eJ+3//9n/e/MY1ljhyuVNoffxysPSQiIgqOW27R51myJO3vXn3VNRumeXORr75yv79sWZ1BG7UFiSgiMAik2CwR4c2qVQkHgZgS06mTDiRROwmptYmIiCKtnUyXLml/h3YPidTKl9fXW7Xyvt1LL6VwB4koVBgEUmw5dsz3fQcOuEpIGJcuiVy44Co0X6CAa5H8sGFB3FEiIiIHZAc1Mmd2zYaxr6n3tHJlMneOiEKJQSBFj5SOBCLgO3nS/baXX46fIObFF/X51Kki//yT/P0lIiIKh+QEgdCyZfz1hZ7rABPKtk1EjsEgkGKLr6AtY0bvvZujRrkuZ8igz+vUEbntNj1N9LPPgrWnREREoS+llBAkRzMwPRTOnXPfBmWU/v47Zc9DREHHIJCiR0qmudxwgz6/etX99gYN4m+LxzejgVgE7/k3RERE0dZOGnnz6vN+/eIHgRUr6g7STz5JyV4SUQgwCKTYatx8pcXGej9vI4FFi+rzXr3cb2/bVveIor7gjBnJ32ciIqJAzXRBgrOEyjQEIgg0WUIx2vfTT64gEMnTTJZtlJRIaN0gEYUdg0Byvu++E9m4MTCPZV/zZ7Kc+RoJxGU0cJA1q/vj3HijyLPP6sv/+19g9o2IiCg55s/XicuqVXPV9EtISoLA995zXX7gAZH77nMFgS1auO5DTV0iciwGgeRsWFvQtKn3aZnJ6eEsVsx1GaN4niOB9mktSAqzY4fvdNrIkobnWr5cZN68xPePiIgo0P79V6R+fddMlz59fK/9S+maQChSxNVm2oO98+d1IGgktSA9EYUUg0ByNpOOGtNOUMIBjR2SsZw6lfJi8faRwCNH9LkpBwHDh7sue2YNNVNF27TRl3F++HDy9omIiCi5TMZOewfo++8HbzoofPut7/uyZ9fnCU1LJaKwYxBIznX0qPvIXOHCIrlyiXToIFKwoMhDD4n88EPSGjf7ffbLZu2fnX30r2xZ74+HWoEYXURw+sor/rwqIiKiwFm0SJ+XKKFr+UHPniJffeX7b1IaBDZqJPLhhwl3tnJNIJGjMQgk57KXZ/CEou5IT924scgbb/g/xcU+Emi/nClT/J5Le+Bn39YOawXHjtWXp0wRWbbMv/0gIiJKqfHj3dfPY2rm/fe7RgjRYWov3h6I6aDGE0+4X0fpJPsae44EEjkag0By9kJ3f7z1ll4M789IYJcu+vzRR923M0GevdFC42nccovvx7z3XtdieDw+Gz4iIgqFESNcl0uX1lMxp08Xuflm19r36tV10phATgeFnDndrw8cqM85EkgUERgEknPt2uX7vrp13a//9pvI9u2JN24I2LZtE5k0yb1wvLdGyxSHx0L3O+9MeF+HDNHbb9okMnFiwtsSEREFwurV+vyll1y33XRT/HYI6+rt2wQiCLQngbEvoTBr6O+4w32dPRE5CoNAci6TrMUbZELztobQH+gtRcB2+nTCI4EmIBw6NPEGE72sr76qL/fty4aPiIhCB2v07LBUYvJk99tQwD2Q00HtU0DBPLY98DPlI4jIcRgEknMlNK3SLH63M0lk/O3hxCJ6w6xhsI8Emuc39yUGC/ExFQc9rmhsiYiIggVr440qVeLfX6dO/NsuXgzcSKA9EyiYKad2WI84YICeJUNEjsIgkJzp0qWEp4AeO5b4FM3EoP4g5M3rfSTw+PGEk8J4QgH5fv1c6xT9HZkkIiJKKnQ4GmYNoF2+fPFv81buKCXat4+fYM0T2sWaNQP7vESUYgwCyZnspSGMChXcE7X89JNe2+fZ2+lvD+fzz+tsahs2eA8CzZrEq1f93+9OnfQII3pou3b1/++IiIiS4sSJhO9HW7h4sUi3bsE7rnnyeE+m5unMmYRLVhBRyDEIJGfyNopWpoz7SGG2bCKtW+tF8MkJAjHN8+GHdSNmgkAUpPfMCOrvSKBZKG+KzE+dKrJkif9/S0RE5C+Ug/BsGz2hkxSJy4IFM3QwFfXZZ32PBBr/938iV64Eb1+IKEkYBFLkTAe1NzD2HtC9e923S04js2WLa0qnYUYA7T2d/njgAR2cmpIRly8nfX+IiIgSYhKx/PFH4sfJc5QuUAlikGQN2bnHjPEvaDV1dYko7BgEkjOZ8g3FirlusydosU/RrFHD/W8XLUr689WqFf9xTZIYfxPD2L33nk5es3Wra50gEVEKDRo0SKpUqSJZsmSR3LlzS9OmTWW7KY/zH8uypH///pI/f37JmDGj1KlTR7aYjq5Yhg45kxglGpjX4lkyyRtTvsEIdJZQb1AiwhNqCbJjlMgRGASSs9cE7tnjus0+LdPegKVP7/639gyf/kqTJrBBILKkobSECQjXrUv6YxAReVi6dKl06dJFVq5cKQsWLJCrV69KvXr15JxtHfXgwYNlyJAhMmzYMFm9erXkzZtX6tatK2ewLiuWoJ3AlPw+fXSSFLQVWEYwYYJEhc2bvbeB3uzeLSGXI4d7Zy2WbmDJRbQcf6IIxyCQnAkjaKbhqFRJTwU1o3WeCVw8e7jto4eBCALNfUn1zDMi9erpHyKYHhpNPdBEFBZz586V9u3bS9myZaVixYoyfvx42b9/v6xduzZuFHDo0KHSp08fadasmZQrV04mTpwo58+flylTpsTOu3b+vMijj4rce68efTp8WN+OUainnhJ5/fXQjIYF+zXCoUNJH5UL5msfP17PhHn3Xddtp06JdO+uL+P9SE5nLRFFbxDIaS4Ux0wXQSmIX3/Vawly5fLegNmL1Xqb9uIPE+jZs5Ju25b8kUCToOazz0SyZNFrNjp2jPwfHUTkKKfw41qVa9P12vbs2SOHDx9Wo4NG+vTppXbt2rJ8+XKvj3Hp0iU5ffq02ymioVj5Qw+JzJypZ5AgAdgXX+iEYy+8oLd5+22RJ56I7EQlpoxRxYqJb+uZQC2YbRHKRiBDtr2ME96Hl1/W7eG+fcwUSuQAjgoCOc2F4phpoFWr6oXn9mklnglcXnvNdwFdf5kfAvYpMybLaFJKRHgqVEj3isLEiVwUT0QBg1G/7t27y913361G/AABIOTxSGiF6+Y+bx2w2bJlizsVwvdWpEJw8/jjujQC2o65c3UpoDZtdEfiJ5/obJkISr78UqRnT4lYpgC7vWB7QoGxXag7JDHylzWr7gyFwYPZKUoUZo4KAjnNheIVwfUsz/DmmyKVK4s8+aTrtty5RUqVcl33Z32EJ7NWxj7aaHpO8fgpgSlJr7ziSpGN0U0iohR64YUXZOPGjTIV5Wg8pPIolYOA0fM2o3fv3mpE0ZwO2EvlRJrPPxeZNUtfxkigt6QpqJv38cf68kcf6e/nSJyeaNorBFeJWblSwgqjf4DRQJRSQn3eH34I7z4RxThHBYHBmOYSlVNdYoEJ/jwDsDfeEFm9Wi/utytePGU9nGXL6nP71CAzJRW9ySn1zjt6reLJk/jFlfLHI6KY9uKLL8qsWbNk8eLFUtCW/h9JYMBz1O/o0aPxRgft7WjWrFndThEJ39l9++rLvXqJPPig7207d3atUcPIINYJRtp0fYx2wn+jwAlq1Mj9eqhfa9GirqRpHTroy2gLIzH4JooSqaN9mkvUTXWJFWYdXpEi/m1vT95iTxrjL/RMegaBZr1FckYWPeExTM8z6ilhehIRUTLaRowAzpgxQxYtWiTFPBJh4ToCQWQONS5fvqyWW9TwLKcTbZB18q+/9PRIz2UCnjAq+uGHIqNG6etYM9i/v0SUW25xb78SMmJEeIPAI0dclxGoZ8yok7qNHh3a/SAi5weBgZrmEnVTXWKFKQDvuZjdFzP9B0qUSPrzmSBy48b46wDtRepTAokKnn7alTnUc40GEVEiUB5i0qRJKtMnagWiAxSnC/99n6At7Nq1qwwcOFBmzpwpmzdvVtlEM2XKJK1atYre44vOvw8+0JdNAhJ/PPecyPPP68sDBkhEuXRJn/83+pugcHd+298PlOswQTrKd2CGDBGFXOpon+YSVVNdYrFYvL+jevbyEfb1gkntpTQJaOzFbP39MeGP4cP1OdYFmnWPRER+GjFihOrMRAH4fPnyxZ2+RJKT//To0UMFgp07d5bKlSvLwYMHZf78+SpojFozZojs3KlHmEwGUH/Zk8OsWCER4+DB5M9WCdVIINbEw6uvut+O9fGY6XPihHspCSKKzSCQ01wo3oJ3f7Kewe23uy4np6SDWRNo2IPA5JSc8AWN9c03pzzrKBHFJLST3k4Y7TMwGti/f385dOiQXLx4UU0FNcsqohbK8QDWm/nbbhiYUtuihWtkKhLYgzjU5EvJ3wcTZnMhi2mnTvHbQpTpACyVsE8XJaLYCwI5zYXiTXPxdzqoZxbRpDLJX8yaQPtUzeQWi09KYXoiIko+1JKFBg2S9/dYD4hlJUi28tNPzn8n7AlVPBOl+ZKcpRIphfWK6IDwtmQH05NR5xftLTJ/E1FIJfmXM9YdYGqJpy1Y4JtCnOaSxDVz+NJ84AGRMmVEKlUS6dpVZO1aiQq7diVtFC6BNaF+Mc+zbJk+t69RSOljJxQEojf2t99EmLGWKCoEs40kPzoO/Q2IPCEYMUsJUMMuUl5vUtpJe2dpoNu15MD+mKmgSNCzfXu494gopiQpCJw+fbqULFlSGjZsKBUqVJBVq1bF3de2bdsU7wynufgBa+TQQKHBQs8leiy3bRNZv17kf//TNfSwvsE+nTESmZE5f6e5pLRBO3dOn996qz6/eFGf58wpAXfokGsKa7NmIlWrilSv7t6oE1HECXYbSQnYvTvl2Zx79NDn8+eHv65eYv4roZWk12xvJ9Fx7ASNG+s1/fhtg4Q+ROTMIPDtt9+WdevWye+//y7jxo2Tp59+WmUoMwEcBRmChMce00EegpS77tJpnxEITpsm0rSp3g5BIgKMSO15RmNggjCTqCXYQaBJtW2m2JikLclZa5EU336rz7duZQNIFOHYRoaRmWGRkun7mFVTs6a+PGiQOJp99oi/r9neTgZ6mUNyYZ/QgQ3z5ukEP0QUEkn6Frhy5Yrk+i9hBzKO/fzzz9KsWTP5888/EyzRQAGAIBvz52fO1IlPPvpIZ0CzH/eWLUUQlL/0kh4dRE0oBIgYHYwkyJxpmCQqwWam05gRVNOpsW+fhAymw6BX1LOoLxFFBLaRYYLOO7PGOrnTQY0qVUR+/dW97JATmY5KfztKnQyd1l26iHz6qV7W8uCDgSvNRESBGQnMnTu3qt1n5MiRQxWk3bZtm9vtFATvv697yBD04fzFF30vtMZ7gWAdPYUmY1okMaOA/hbBDURiGPM8GzboczM10/QKh8qzz7pP8yGiiME2Mkzso1rJyQ5tZ2q52kv6OJEJeu2dpolxcmc9MoVi+QXqOH/4Ybj3higmJOmX8xdffKEaObt06dKpgu5IQU1BgrUJvXvrywMHijz8cMLb58+vg0TPgCpSmEYtKfUcU9q4mR8Rpt6kSUyTkvUlibFPNcUIIAroogZmr17Be04iChq2kWEwe7b79ZQGgaVKudoTrFFD7UEn19LFmvKkZlB1ImQC79dPX/7gA5F//w33HhFFvSQFgSjcbgq2e6oZ6hGTWHH2rMgTT+h1cnXruhe19SfAiMQyBKY8QygzZpoEMKZEhJmKEsxsZfaF+SiYa3qdR46MrILFRKSwjQwDEzgEalYIlgZgNkbx4rr9fO01cSSTwRptR1LWPDrZ88/r5Gxo+195Jdx7QxT1ArIyGMVoMR306NGjch3Bis3DiY1aUcLeeUeXg8C8/8mT/R/xMtMb8TcIIn//XQSjtRMnivgI5B3DjF4iA2qoRgLNiN/x4+7TQevUkaCx/1hBDy0S+2BE8PvvRdq00dN6g52YhoiCjm1kkKDTzrMsUkpHAiFLFpFJk3TW5unT9XdxhQriKKbNC0YG63DB75ZPPtG1Hj//XJfAYlZdIucGgXPnzpUnn3xS/vUydI9kMdfsBU0paTA1cOhQfXnIEL3OLzlrJB56yHW5YUORdeuc3ahjcXhSp2KmNAg0JSkAvb87diR9H5KqQAHX5b/+0uejR+veWqQ7x0L5CROC9/xEFHRsI4MEgVnFivFvD0QQCNWq6fZyzhy9vMJpS15MG1WsWHSsCTSQFKZzZz0zBuf33osh9nDvFVFUSuG8CSSofEGaN28uhw4dUqOA9hMDwBR67z09KoagACNDSeEruQjqCX75pTgSMnKi0f3mG30dI6ChatywHsHAMTfZQo8elYDDdM/SpXWdR6NcOX2OUdrx4/VljNo6PU05ESWIbWSQeAsAAxkEQvPm+vznn8VR7SQSiJmyCmZtYDRB9nOszcRyGK6RJ3JuEIgpoN27d5c8JqEGBQaCD9QABAQLSV3nkFDa6McfF+nWTa8zdJJFi0QWLnRdr1cv9NNBzVRQ83imeHyg1z2ghEeJEt73v0kTnSYbzEgwEUUktpFB4Nl22We72Gd1pFTZsqEtVeQPzBYZOzb+PkYTdMKa3z9Y0oKSHUTkvCDwsccekyVLlgRmb8gF008QjGAUEAXik7to3BcEF07rYcNaOF+JU4IdBKL32ATaWJRu6gWGqvH37L1+9VVXZ8Azz4RmH4go4NhGBsHUqe7XmzXTM1xQF9fM4ggEU3PQSctaUCvYLhgdlU6AaaCPPqovd+rkrPeAKEqkeE3gsGHD1HTQZcuWSfny5SWtR123l1C4nJIGwd+PP+rLyJCVnADH3lOKxDCm0USmM5SZMLUHUVAeCUmc4LffXJexKDwpU2ADsdbBHLNz51w9j4H8QeENpvWglmOPHu6320fWx43Tvb3duwd3X4go4NhGBsGAAe7XMb0eSVyC1TnnpADEvjYRs0Y6dJCohWmhKAGyaZPIm2/Gf9+JKLxB4JQpU2TevHmSMWNGNSKIZDAGLjMITAYEQGfO6MtJXQvoLQi0Z9lEOm1kHEXwgSkl7dqJbNnijIXXZg0gEqKEIyMYjgEStCAIR3rwzZuTln47OYYNw6Kh+JnnkNgHgeHgwa7OADT42C8iihhsI4OYFMVAjdVgcGIQaLJn43dCtGfOLFRIt4EYTHjrLd1pjcQxROSM6aB9+/aVAQMGyKlTp2Tv3r2yZ8+euNNuZDikpC/67thRX0bPV3JHovA43rJQmkYNwQd6TzH1ERm4nODQIVdWtqTC6F1KmXWBR464SkQEu64SnhMJDryNZCIxkKmZaKb98P8UUURhGxlge/YknNgrkEx76bkGEdP0w/FdbA9Gk9NORiJ0kpoEPZjVtG9fuPeIKGqkOAi8fPmytGzZUlKntEAraciMaRocEwwmR6tWOoBs1Mh9vZl5n7B4HlkoEXxgLR4Wm4eTfcTtjjuS/veBSEy0a5erRISZDhrMEhH+wPu0fLl7FtFjx8K5R0SUBGwjA+yDD+LflimThHQksGZNPSvju+8kpJDd27jllqT/fSSUiPC2z/itUrKkznXQooWzRmaJIliKI7d27drJl04tORCJPv7YtSA9d+7kP07RorrOIBopM6rl2QigJ/H++10ZKxFIISulSYoSSvZsZ0gNnVSB6IRAww54/YUL68v2YxcuWOtipjthZLB+fd8lQIjIUdhGBhjqx3nyyEUQ9CDwzz/1+SOPiJw/LyGD9eGe+xYLMmcWmTFDd2wjdwBmyRBR+NcEohbg4MGD1brAChUqxEsMMwRFzsn/KY3LlrmStqSUyWyZ0JRGBH2mLAOmuKD2EKZlTpsW2l7DrVtdawDshe79FYh9zZhRn2OajxmNLVJEHOHvv0XWrdMZ09auFXngAZF580SyZw/3nhFRAthGBpB9mQM6w/AdCMFqq+yB1pUr8YNN7A+Sl/TpIyExf37KcgXYj1+kQXI0BH8ob4XcBo0bi5QvH+69IortIHDTpk1yx3/T9zYjkQYlX9++rstPPx24I4kRLmSW9JZUBNNFsdbM9GzCV1/p0bhQZuJCjUDPek9JEYgfAWY6KHob9+93xnRQz5IZ+NGD+olr1ojUqSOyeHHCNSGJKKzYRgaQCfoAgYD9ejCYEhGAwuXoWPVcH4jABDNpcuaUoDNtVHLXA5p195Hq5Zf1iCA6yxEIr14d/AzeRFEsxUHgYvwIpcAwhcExIhXIqR4IkD780Pf9yA6KkSaMeqFXE5kokYmrQYPgpN325p9/9Hlyp8AGIgjEa0XSAfT4mkQzTptyg8Yf/+cQCCJtNoJ4BNDBWhNDRCnCNjKA7DNk8H2NqaGYPRIs9lkpaBfMmnEjVy7ddiF75ZQpElT2UTwkE0uOG2+UiIZ2fuJEvTZ+40aRnj31bxYiSpYUL6QaNGiQjLPPU/8PbnuP87b9hyydxogRElLoScMaQnzBYsQQ0yzguedCswAb0xzNuop77pGwrjsAe82+UPTuJtWdd4osWKD3d9UqFpMncjC2kUGYMYLp8KaIeHJnj/gDbaLpCDTBnz0INGv4UYfXs2xFoP3wg+uyZ0khfzmtUzM5ihVzrQtFxzk6sYkoPEHgqFGjpDRKDXgoW7asjBw5MqUPHztQxN148slw7okOQjEaiem9we5l275dBzUpSQoTqJFAb1NlkJ3TiTA1dPp0/bqxfhO9o0TkOGwjA8QefGFdWKiYdYBmJNDeYfvoo+5tFwqbBwOS7z38sOt6lizJe5xIzA7qDeob239DEFF4gsDDhw9LPi+FWnPlyiWHIn3+eSh9+qlrDUK4v6hRVxA1CuH//k/k4MHQpfu21zQMtdtvj3+bk9YEekLRXIzcmlpK3upnEVFYsY0MkDlz3JPChIrJPI3yBJ4Zoz0TxaAD1x4kBop9dkr+/Mn/jRDu3xaBZJaqmOCciEIfBBYqVEh+NTXVbHBbfnxZUeLsjYq3GkjhgODCNHAFC+r1Z4GGKaCffaYvI2kNsnKGs3Hztl7C6dk3335bZ01D0oLHHgtPeQ8i8oltZIAMGxaeaY1mqYL5bjVBhxmNO35crwk0l5FhO5AQfJpEZXfd5V43NpaDQLMOnjUDicIXBD777LPStWtXGT9+vOzbt0+dsB6wW7du0qFDh5Q+fGywB35PPSWOgEbW3sNmr+MX6HTXZkoH5von1333pXx/0IBHWqOJ6aqYForpu1hbaX6MEJEjsI0MEKyDBlPbNlRKlHDvrDXtoukkRcZQBH5m+cu77+pyS8H4fYAOd6eULQo3k7THPk2YiEKbHbRHjx5y/Phx6dy5s1z+r6csQ4YM0rNnT+ndu3dKHz42mMXlTlu4jYXuJUvqy0uWBHd6T0pfNxbK//67niqTXBhRi0RYk4sgvVUrLEDSyXVatw73XhER28jAZ8bs3Dm0nyuzJMAsbzlxwvtU0Gef1dlLUcYBiWuwz+ic++47ES9LZpKcDAePkZwaupHUqZkUDAKJwj8SmCpVKpUF9J9//pGVK1fK77//roLCN954I+V7FytMryHW3zkJekBNII8pocaBAyJ//ZXyx8fIFdSuLQGBQDAl2TydmgTGH088IWJG3rFoPtjpyonIL2wjA2D9etdllMUJpW3b3ANRMxJ45Ij7dujINJlKsXwCidVQxw7r3NG2X7iQvOffsEGft2ghKRaNQaC9xjERhTYING688UapUqWKlCtXTtI7OZmG05jF5qYQqtOYbJ1m3v3KlSKFC+spKQj0MVroWTzXX6hNCHfcIY6Q3NfhpORCzZrp9wojgWPGhHuPiOg/bCNTwJ79ONS/L0wnpVkTePGi70Ri3spiIXjElE7UtksOEzzWqiUpFk1BoMkKimR6nr+p7CPHRBT8IJCSyd6bGM7MmIn1tpmGyCzOR8CEgvIIEpPbQ2m+qGvUEEewj3ZGIkxPQirxNm1cdR7NaCsRUaT65ht9fuut4UtAsnOnPjdZmL0Fo7jNPvVzwgTXZSQ+S2pwYu+YDERnaTQFgTVrxk8MgxkwWKP5zDOR36lLFAIMAsPNLGrOlUscyQSBS5fqBsQ0xnbebvPH4cMpqw0YaNEwgo33y95r/scf+hw/PtgoElEkMmWKwrHWee9e9/YhXTp97qs4/ODBrsuPPCLy22/e7/OHPcFMILKtR1MQaN4He0bsxYv1+fjxIk8/zcyhRIlgEOiUIDClC76DxXO/zFQYNGZdu7pnT0sKe+bR3LnFESJ5TaBnXSszhemnn0S2bBHJm1f3nAaz5iMRUaCZRCymDl+46tGhDI+989JXRmqsz0bHZqFCIlmzilSpIjJggL6vVy/3klCJ2bcvujopA8kk5rEXi7eXeUJnaMuWSTveRDGGQWC4OT0I9JV+GRkpUZcOkjP/3j4NNkcOcQSn1wRMToHjceP0WhT0KGM9Z7VqrtFBIiKn++or1+Vbbglf5+DGje5tl68i5UgQg+9YU9sPXnnF/fGQwdmfmq6BLjzfsaM+v/tuiXj//hs/ODbvSdGiug3ELCUk6zGd10TkhkFguJkvJ6cGgefOeb8dI0v27Fz4sh0xQgccs2f7nxTGW6rtcPHsacXagki1bJn325HVFT3b9hqNRERONXVqeGdqmGLxefK4X0/KyBzWFT74oOv6L7/oMhKJMR12ZjQypVCHGOvETc3FSFa8uHuHJ5is5ZgK+u23+j1auFCkeXPfQTtRDGMQ6JTerEAWlw0kXyUXEADaA1eMCr7wgp56iJ63NWsSflwzpcZJ7FNJPKchRRpfI7hILoDsaQ0a6Ex2XCdIFHF+/vlnady4seTPn1+VoPgWP3htLMuS/v37q/szZswoderUkS34bo5EWI8OjRuH5/lNVk/TsYYSSZDUou0PP+x+HY9nHyH0BslkAtleYk0g2oBoWPpgZu6sWBE/2zqmgOLzMnOm/p3yww8izz/PrKFEHhgEhpvpxfIMQJzCvl6vbl33KZyeo5f2gOLee93n6nsyU2UwrdQpoqFhTAx6oJHNFe8V1qfgPfWsd0VEjnbu3DmpWLGiDDPZmj0MHjxYhgwZou5fvXq15M2bV+rWrStnzpyRiGJvU1D/NJyzYbDGz75PJjGJv+rUcV0uWVKfDxkiMm2a778xo43mucnFfJbtCXPM7J2MGfU5Oju/+MKVLKZ/fx5BIicHgTHVwwlmikI4Ul/7o2pVkddf14us7XWR0AAmFDRhEX29er5HOE2WMicHXv/7n0QdTEvCj45PPtHHftEivU7QV6Y7InKcBg0ayNtvvy3NUBfUA9rIoUOHSp8+fdT9qN07ceJEOX/+vExBCv1IYh/lQXsSDmXK6POff9bnpnMzqSOBN93kujx6tJ6iaBLJ+Pr+NaOPWENI7kwHsr1jw6yztJfbevxxkfff15eRoGf4cB5JIqcGgTHTw2mcOuWsdXHegjV8cSIrm73RQxDoa/Ry0iRdKwmjfXfe6X0bU78uuQV0g2XQIJGGDXVa7xdflIhles2Rotzbe4qpu6tW6dqISIGOQBDBIYvsEkW0PXv2yOHDh6WeLWhKnz691K5dW5YvX+71by5duiSnT592OzkC2hIjXG2kmfHiWcfX1A9MzqwaBCuff+56jPr1E65da34nkIvpQF692nXbkiXeR2lffVWkSxd9GedYJ0hEzgsCY6aH0zBz/U0xdiezN4JokH2VdrjrLpH/+z/XQm1vC7JNXUR7ghgnwBRJJLZBWu9IrqmEJD0zZugR3Bo1vPdcV6ige9orVtTrH9Ej7U+yAiJyLASAkMckMvkPrpv7PA0aNEiyZcsWdyrklOmHc+eGv7PQHAtTrsEsZUBytKRA1lAskzAjewhiOnTQ1//5x1WCwlviuPLlk7nzUSxzZn1euLDrNlOuylvm1aFDXZcRdGNpBFGMc1wQGOgeTkf3ctrnrkfCCIz9uOELGIEgFmJ7JlDBOgaTihq8Tb8wQS+mm1JwPlcYBcySRQeEqGmFnmdvPc0oHdG7t76O6aEmeQwRRSwsp/DsRPW8zejdu7ecOnUq7nTAJD8JN1Oo/dFHw7cPvkb8khoEmrqt6BQ1o1gffOBad/jSS/G3N8XPWSMwPtMJbS/FsXmz71IiGNE1o4ZY14n18MhqThTDUkd7D6ejezntKaDLlhXHsx93k9AmWzb3tQ7myxZByFtv6esoKv/rrzrQxRrPXbv0dWDjFnwY8cOPj1q1vN+PHyQDB7qub9igF9jjByNGf1lXkChiYIkEeLaJR48ejdd22jtTs2bN6nZyVHkiFP0OFzNrxV4eIrl1ZfGdak+ohssTJrgSl0yf7r0MwrVrSX+uaGcv4WSS9Zjj5GvqcOXKeg0h2kKMsiKrORKlsXwExaiICgKT08Pp6F5O+5eVKRXhZOg5w3RJe/Fe49139TlqIZlsXT17ilSq5FqcjZ5OjE4hCc7Bg/p2FnF1jm7d4t+G6brooHjuuciYskwU44oVK6YCwQW2WnCXL1+WpUuXSg0zNTwSzJnjuhzOLNJm2qF9ZNIzOEzp+m0z2jhypO4sRe1dBDTokLMHg+Ri73z2rGdszxjqCbkMzDRj+PprPT0UU3KJYkzqaO/hdGwvp2F6rkzKaCfD6B8Sp5isZnYI+NB4/fije4BrajthbaA92Y95D4sVC/Zek7+Qrhzv4aFD7rejl3XMGL1e0GlrOIli0NmzZ2XDhg3qZJZK4PL+/ftVh2jXrl1l4MCBMnPmTNm8ebO0b99eMmXKJK1atZKIYS+dEM712fYkI/YZO4FMVNO6tT7HjA2MTGFtm32tm+dsG3KfposAzj5KixlKCcFMJfz2GjVKz0bCtFtkP7dnoyWKAREVBEZND6edWZycnKklkcDbOge7UqVCtSfkL3S2vPGGXk+ILK7ffacbTay7RYICJM4horBZs2aN3HHHHeoE3bt3V5ffwP9bEenRo4cKBDt37iyVK1eWgwcPyvz58yUL/k9HCqxPhvvvD/ee6Lq4wfTRR67LZkqovcPNZAkl944B877gWNlnUyUWBJpObcxwwZp4rCHEY2CaKEtIUAxxXBAYEz2cdiZjY7ROi0Rwi/IDvvgqM0Hh9eabOhEQfmQ+/LAumYF6WcePizz0kM7+aqb0ElFIoT4ulkF4nib8t74MbSXq6R46dEguXryoOkqRTTuimORU4UwKYxw7FvwppwnVQbSvf6P47wtGAe0zWJIycowRQHR2ol27elWXkHj6aWQU5JGmqOe4IDAmejjtzKimKUgbjXzUfFRQT5CcDz8g16wRMZ0tyGpXtKhI27bB/4FERLHlyBHXZW+1TkPNsyMzGMXbsZ7eF5OIjby/L9u2udZrJuc3BUYOMeMFnZ8mSQ9ml+3ZwyNOUc1x3ywx0cNphyQp0Q49bXZmugtGARkERg5MCf3iC/3+oYFErymKOU+eHO49I6JoghqnKSnFEGg7d/oOUgMF9VopaczoH0YCzXuC7J/JgUAbgw0IBpE3AqOD+O2SQPkxokjnuCAw5mzZos8xqhKtUCQXUwpN447pPfjSxnSfSC7IHovQUOL9Q4kPU/j45Zd1DUL79JlTp8K2i0QU4UyCMackcbvttvhld4JVM9jTwoWBf65oceed+hzr+bBUAUxG8uTCbxXMekEHPZZE1Kwp0qeP9wL0RBGOQaBT+LOQOZKhdw0jR2ZqDxo8BIcUuUzBY5Pm/NVX9WWUEUE2O9RkQlZRNKRERP6aN0+fIyOxE5w96349GGv47VlImzZ1XWZm0MTboFWr9Lp1exH5lEB2ViQmMonrUEcXnZ74DUMURRgEhpO9IQnEF5fTMeiLLvaU3GbtJ0Z233tPX1+7VmdfQ8F5nC9ZwqLHRJQ4M+rSqJEzjpZnds5A1Qi0sxeRR01ewymjoU7uPF+92jV6HKhkc4UK6bWGY8fq65gW+vPPgXlsIodgEBhO9oQa0VoigqJXYtNj6tTRPanoRceIIHpS8WMKdSbffltPc/KsSUhEsc2e6h8ZG53As30ORvF6e2DZoIEuW4DOYZaHSHw6qOcoXqCgUxOZQg2UK8HSh2ef1WU9LlwI3HMRhYGt64lCzvwAxjQQro2jSINgDsV1UTT5ypX49/fooTPeYQQQCWVmzhQ5fFgnljHJgQC1Bx97TK+9QO8rRg5RCJj/J4hijxnRcdIMGfsoHQSjfIC9DET+/DpfAAqa+1orSN5nFwW79jCWPhjIko31gggK7dN5iSIEg8BwOnpUn3PBMUWiTp301Bv0kiOI84QfMgjkMAKI08iROiDctEkvvMcaDqTgxnWc7BBYVq0q0qyZHg0IZO8uETkXOovASZ1AGA0aN851vXXrwD8Hgr3t2/Xl9OkD//jRyFtCPbQ7oYKENKgr+P77Iv36ibRpE7/DgMjBOB3UCdNBnZACmyg5i/I7dPBd5gSjeXboKUVB5FdeEZk6VWTXLv1/AD+umjTRPbgomgwYWfzlFxQKFSlZ0rXOkIiiG5J8QOPG4hiYpYCOqs2b9QlTNYMB33U4kX8KF45/W5EioTt6WAeP32+oUfjUU7rk1TvvhO75iVKIQWA4bd2qz4sVC+tuEKWIr04Mf9a5YgoUGs9vvxX54w9d4wnlJdAjPmSIa7sffuCbRBQLMLoC990njoJ6xGXL6hM5g7fpwsFI2mMS9Xz8sfvtGAVEZyY6KZHAB+tZ+/bVo9gYGTSfZSKH4rh1OFmWPud0UIpk9mCvd2+RLFlErl8XyZEj6Y+FxhONKU7oEcfo4QsvcL0FUSw4d855SWHIuczMEc+lBMFYp/rnn7pNQoclykd06+aa8YL17+jMtAelAwaIDBok0ratyPDhnOJLjsQgMNQlIdatE6lWTRfdNiOBmGpCFKnQ6GJtH5IYFC8e2Mc26zvQABNRdFu2zHU5WFMuKXqEat0oEtCYhDOoeTxjhqvmsX0EEssYMJtl8mS9zGH9en2OE5ZOoOQJlkQw2Q85BKeDhlKNGjrgM3VnduwI6dMTBXWBfqADQEBnCRw/HvjHJiJnwSiL4aTEMORcrVqF9vmQDO3JJ/WMF09ICoMlDpi9gjq5HTu6RiZRJqlpU539GqOIyP5KFGYMAkMJvUIwerQ+v3pVn7MOEFHC6w1Ra5CIohsyBsNdd4V7TyhSTJok8vrr+vLzz4tjoBNjxAg9xfmNN1y3nzghMnSoXmOaM6cuSE8UJgwCQ+XgwfjrHo4cCU1dG6JIlSeP6zLWGRJR9HeUYsockb/BFmr1zZmj6/Y5DUYC33xTz2ZBNmwkOcOIIOB6mTL6NWANPernmlwRRCHAIDBUpkxxXUbmQxSbNaMbHAkk8g4ptw3TaUJE0cf+45dBICUF6io2aKCnajoVpokiiRrWBaIW5oIF7vcjSGzeXGTWrHDtIcUgBoGhgoXE9hEN1FjzNtpBRC72oslcQ0EUvezT4qpWDeeeEAXfAw+ILF+uM4ja1xdilBAjgzhhgABTXJcu5UwYCgoGgaGycmXSat0QkXsgaNYLEVH0+f5712WUhiGKdtWri/TqJXL6tO9lRMghUaeOSOHCIi+9pDPMEwUIg8BQSGwtUzDq2hBFC5MqfvXqcO8JEQWLmR6HTMNEsaZxY++3P/20nuaKgPCTT0TuvFOkYkW9DhIZSFF6jCiZGASGwpo1rsvIBkVE/itbVp9v2MCjRhStFi/W56ybS7EISW2wFhadIfZkgSgp9s8/eq3gQw/p2zZuFBk4UKRyZT2VtH59kY8/Ftm1K2y7T5GJQWCoUhgbSBls16VLSHaBKGJVq6bP9+4N954QUbBnzPgaESGKZiVLisybp9cKzp+vOz9N3UzkkMD/C0yZRjs4frzr71BqDNu//LLIrbfqABKXf/xR5Pz5sL0cigypLCv28tGePn1asmXLJqdOnZKsWbOGptYZMhuiLsyKFe6LgGPv8BMlDdZAYAoMXLvmKiBPESnk37/k/Pdo3z7XNNCTJ0WyZQv+cxJFeqcJSkz8+6/I7Nm69MSvv7rqT5v19FhPiMypGC1EgIiEM+R4p0P0HcxfU6FgUtsj/a+TUxgTORE6T+zlVYgoeksoMQAkShw6Q3PlErntNpFXXxVZskQHhN98I9Khg84silJkGF3s2lVvh44WrDG0162mmJYm3DsQ9Q4fdl1u3z6ce0IUmeyZAjHtBY0ZEUWPL77Q5yiYTUTJgw6UZs30CbPMtm7V00LnzhVZtkxk/349lRSn/v1FbrhB16tGwPjoo+51eSkmMAgMto8+cl1Gil9AodBHHhEZOTLoT08UFVBo98QJkV9+0esdiCj6agQ+9li494QoOmDaJ9YV4oSRQqwPxLpDMwqIINDuxRdFSpTQZSuQnOmee0RKl+b00SjH6aDB9uGH8QvCoxjolSu6CCgRJQ5rGuDnn3m0iKIJ1jUZHTuGc0+IolemTCJ9+/rOW4GgcedOkc8/179Ny5TRNazxe/Xtt/V9zGERdRgEBnvhLhJZgOfoRRoOwhL57a679PnRozxoRNHkjTdcl2+/PZx7QhTdENyNGqWnia5f70oec+iQXk+I5DIIFGvX1hlJcdt334m8/roeRcR0UwSLKFo/darI7t0MDCMcs4MGM/MZpnt26qQvYyg+Y8bgPRdRNNuyxZUghhlCIxqzgzpfSN8jdIji/zRq6KIeGhGFxl9/6aUWmTPHv+/yZV3j+v33dakK/D+1Zx41THKaChVEqlYVqVRJB4wc6IiI72AORwXTokWuywwAiZLPXjz3jz/0VBUiivwfocann4ZzT4hiDxLCJJSQrUYNncMCzp0Tee89PX0bgxooWP/777rjBics1Rg2TG+LhDM9euiC9uRoDAKDZccOkenT9WUU+CSi5LP3KmIaC4NAosg3eLAeBcTIQYsW4d4bIvIFo4UDBrjfhmAQs3RQugmjhr/9pmth4//0oEEMAiMA1wQGS7dueq40Miw99FDQnoYoZuTPr8/R+0hEkW3XLpERI/Rl/GAkoshLNlOlikibNiJDh4osX+5ey9fUyCbHYhAYDBMnisyZoy8PGRKUpyCKORgtMNNBiShyoYP02Wf1GiMkfULJJCKKfCgzYf8tTI7GIDDQ0AvSpYu+3L27SOXKAX8KopgOApGxjIgiFzpHlyzRa4dGj2YtMqJogeyhZtoo1hCeOhXuPaIEMAgMJCycRY8mzu+4g1NciAIJhWvh4kUeV6JItXatSM+e+jJ+LFasGO49IqJAQlIYJJ05flzXGCTHitggcPjw4VKsWDHJkCGD3HnnnbJs2bJw75IeAdy2TddSQUYlZFciosBmMkublkeUKBLbSXTgtGqlE0dgvXyvXuHdHyIKPNQeNOt8P/hAr/8lR4rIIPDLL7+Url27Sp8+fWT9+vVyzz33SIMGDWT//v3h26mvvnLNf8Z5kSLh2xeiaIR6RoAMZEQUee0kRgiQORt1r1BsOnVE/gQhosS0bi1SvryrSD05UkQWi69atapUqlRJRpjMYoJalbdJ06ZNZZAfWcYCUoQRNQAx1I2F7fv2ifTrJ3Lpki4OP3x48h6TiHxD6mnULbrpJpExY6J/XUWUOn3+vGR78snQFCKPYSlpJwPSRl6/LjJ7tl4egVTyGzaIfPKJvm/SJP0jkYii1xtviLz1lr78+ecpb/MS2yYQj+GQ51HtZPv2LBbv6fLly7J27Vrp5TGNpF69erIc6Wm9uHTpkjrFHdzTpyXFXnlFN2p2998v8tFHKX9sIoqvQAF9fvKkSPPmPEJEAWong9JG4gdOkyY6E6hn+SQGgETR75lnXEHgk0+Ge28oGorF//vvv3Lt2jXJkyeP2+24fvjwYa9/g17PN998M7A7gsQvWbLoItY4v/dekc6duQ6QKFgKFRJ59dXonw4aeZMzkubKFZGVK8O9F1Etqe1kUNpIBIG1aukpnyg0jRHFxo1FWrYM7PMQkTNhWRSCQH/WIvvb7gVyOysMz+nvdmgnfQxsxXQQaKTyGEbFrFbP24zevXtLd5RrsPVyFsIPypQYNy5lf09ESYP/3++/z6MW6TDKhORZ5Jh2MihtJKAMBBHFrr59w70Hkel0aNrJiAsCc+bMKTfccEO83syjR4/G6/U00qdPr05ERETRLqntJNtIIqLYE3GpudKlS6dSXS9YsMDtdlyvgaQRREREMYztJBERRd1IIGDaStu2baVy5cpSvXp1GT16tEp73bFjx3DvGhERUdixnSQioqgLAlu2bCnHjh2TAQMGyKFDh6RcuXIyZ84cKcLafERERGwniYgo+uoEphRqH910001y4MAB1qkiIgohk3Tk5MmTqhYdOQ/bSCKi6G8nI3IkMKUwiggByX5GRETJ+h5mEOhMbCOJiKK/nYzJIDB79uzqHOsII+FHiOkRiJSRS+4vjy8/D/z/ltAoU+HCheO+h8l52EYGV6S1kZG4z9xfHt9I/jycClE7GZNBYGoUrxWU4MgWER8GA/vK/eXx5eeB/9+i4fvBfA+T87CNDI1I+z8bifvM/eXxjeTPQ+ogt5NshYmIiIiIiGIIg0AiIiIiIqIYEpNBYPr06aVfv37qPBJwf3l8+Xng/zd+PxDbHLaR4cLfITy+/DxE3/+3mCwRQUREREREFKticiSQiIiIiIgoVjEIJCIiIiIiiiEMAomIiIiIiGIIg0AiIiIiIqIYEpVB4PDhw6VYsWKSIUMGufPOO2XZsmUJbr906VK1Hba/5ZZbZOTIkSHb10GDBkmVKlUkS5Yskjt3bmnatKls3749wb9ZsmSJpEqVKt7pjz/+CPr+9u/fP97z5s2b17HHt2jRol6PVZcuXRxxbH/++Wdp3Lix5M+fXz3Pt99+63Y/8jbhmOP+jBkzSp06dWTLli2JPu4333wjZcqUUZmlcD5z5syg7++VK1ekZ8+eUr58ecmcObPa5sknn5S///47wcecMGGC12N+8eLFoO4vtG/fPt7zVqtWzZHHF7wdJ5zef//9kB9ff767nPb5pchrJ9lGBh/bSbaTbCcnxGQ7GXVB4Jdffildu3aVPn36yPr16+Wee+6RBg0ayP79+71uv2fPHmnYsKHaDtu/9tpr8tJLL6mDGwpoWBGQrFy5UhYsWCBXr16VevXqyblz5xL9W3yQDh06FHcqUaJESPa5bNmybs+7adMmn9uG+/iuXr3abV9xjKF58+aOOLZ4nytWrCjDhg3zev/gwYNlyJAh6n68FgTcdevWlTNnzvh8zBUrVkjLli2lbdu28vvvv6vzFi1ayKpVq4K6v+fPn5d169bJ66+/rs5nzJghO3bskIcffjjRx82aNavb8cYJPzaDub/Ggw8+6Pa8c+bMSfAxw3V8wfMYjRs3TjVUjz76aMiPrz/fXU77/FLktZNsI4OP7STbSbaTEpvtpBVl7rrrLqtjx45ut5UuXdrq1auX1+179Oih7rd7/vnnrWrVqlnhcPToUZTssJYuXepzm8WLF6ttTpw4YYVav379rIoVK/q9vdOO78svv2wVL17cun79uuOOLZ535syZcdexj3nz5rXefffduNsuXrxoZcuWzRo5cqTPx2nRooX14IMPut1Wv3596/HHHw/q/nrz22+/qe327dvnc5vx48er1xRs3va3Xbt2VpMmTZL0OE46vtj3++67L8FtQnV8Pb+7nP75jWWR3E6yjQw+tpOBw3bShe2k5bh2MqpGAi9fvixr165VUbYdri9fvtxnNO25ff369WXNmjVqeluonTp1Sp1nz5490W3vuOMOyZcvn9x///2yePFiCZWdO3eqYWtMJXr88cdl9+7dPrd10vHF52PSpEny9NNPq9ETJx5bz973w4cPux0/DPvXrl3b5+c5oWOe0N8E8/OMY33TTTcluN3Zs2elSJEiUrBgQXnooYfUaEOoYAowpmmULFlSOnToIEePHk1we6cc3yNHjsjs2bPlmWeeSXTbUBxfz++uaPj8RqNIbyfZRgYX20m2k96wnYzOdjKqgsB///1Xrl27Jnny5HG7HddxkL3B7d62x5AtHi+U0GnUvXt3ufvuu6VcuXI+t0NwMnr0aDUVB1PuSpUqpYIVrCcKtqpVq8rnn38u8+bNkzFjxqjjV6NGDTl27Jjjjy/WV508eVKtA3PisfVkPrNJ+Tybv0vq3wQD5tL36tVLWrVqpaZZ+FK6dGm1bm3WrFkydepUNf2iZs2aqrMh2DAFbvLkybJo0SL58MMP1VSM++67Ty5duuT44ztx4kS1zqBZs2YJbheK4+vtuyvSP7/RKpLbSbaRwcd2ku2kJ7aT0dtOppEo5DnKgwOf0MiPt+293R5sL7zwgmzcuFF++eWXBLdDYIKTUb16dTlw4IB88MEHUqtWraB/GRhIAILnLl68uPpBig+3k4/v2LFj1f5jFNOJxzZQn+fk/k0gYXQAo8TXr19XCSgSgkQs9mQsCFAqVaokn3zyiXz88cdB3U/MqTfwpVy5cmU1YoYRtoSCq3AfX8B6wNatWye6ZiEUxzeh765I/PzGgkhsJ9lGBh/bSbaTnthOfhy17WRUjQTmzJlTbrjhhniRMKZ3eUbMBhZgets+TZo0kiNHDgmVF198UfXUY+ohpmwlFX7khWLkxBOyQCIY9PXcTjm++/btk4ULF8qzzz4bMcfWZF1NyufZ/F1S/ybQASAWKGOaAxZCJzQK6E3q1KlVNq1wHHOMBCMITOi5w318AZkckbwoOZ/nQB9fX99dkfr5jXaR2k6yjQw+tpNsJ/3BdjJ62smoCgLTpUunUlibDJAGrmPKojcY6fHcfv78+WpEIG3atBJsiNzRO4Cph5iShnV2yYE1PviPGWqYNrdt2zafzx3u42uMHz9erftq1KhRxBxbfBbwH91+/LBeA9mmfH2eEzrmCf1NoANABBgIupPzAxH/JzZs2BCWY45pzRj5Tei5w3l87b31+K5DRrdwHd/Evrsi8fMbCyKtnWQbGTpsJ9lO+oPtZBS1k1aUmTZtmpU2bVpr7Nix1tatW62uXbtamTNntvbu3avuR/aztm3bxm2/e/duK1OmTFa3bt3U9vg7/P306dNDsr+dOnVSWYCWLFliHTp0KO50/vz5uG089/mjjz5SWQN37Nhhbd68Wd2Pt/Kbb74J+v6+8soral9x3FauXGk99NBDVpYsWRx7fOHatWtW4cKFrZ49e8a7L9zH9syZM9b69evVCc8zZMgQddlk00TGKHw+ZsyYYW3atMl64oknrHz58lmnT5+Oewzsvz2r36+//mrdcMMN6m+3bdumztOkSaPer2Du75UrV6yHH37YKliwoLVhwwa3z/OlS5d87m///v2tuXPnWrt27VKP9dRTT6n9XbVqVVD3F/fh87x8+XJrz549KjNs9erVrQIFCjjy+BqnTp1S/6dGjBjh9TFCdXz9+e5y2ueXIq+dZBsZGmwn2U6ynZwbc+1k1AWB8Omnn1pFihSx0qVLZ1WqVMmt3AJSwteuXdtte7w5d9xxh9q+aNGiPn9cBQN+6Hk7Ia27r31+7733VJmDDBkyWDfffLN19913W7Nnzw7J/rZs2VJ9OPEDIH/+/FazZs2sLVu2+NzXcB9fmDdvnjqm27dvj3dfuI+tKUnhecJ+mfTBKMuBFMLp06e3atWqpb4k7LD/Znvj66+/tkqVKqXeJ6R2D1QQm9D+IpDy9XnG3/naX/wARZCOz0euXLmsevXqqcAs2PuLL2E8F54Txwn7gNv379/vyONrjBo1ysqYMaN18uRJr48RquPrz3eX0z6/FHntJNvI0GA7yXaS7WThmGsnU/23k0RERERERBQDompNIBERERERESWMQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgUQi0r9/f7n99tsdcyxSpUol3377bZL/bvv27ZI3b145c+ZMUPYrkh09elRy5colBw8eDPeuEBFFHLaT0Y/tZGxhEEghM3LkSMmSJYtcvXo17razZ89K2rRp5Z577nHbdtmyZSoQ2rFjR1S/Q4FuVPv06SNdunRRx9lTqVKlJF26dGEJgvbu3avezw0bNki45M6dW9q2bSv9+vUL2z4QESWE7WR8bCdDh+1kbGEQSCFz7733qqBvzZo1bsEeRq5Wr14t58+fj7t9yZIlkj9/filZsiTfIT/99ddfMmvWLHnqqafi3ffLL7/IxYsXpXnz5jJhwgTHHtPLly8H9fFxbCZPniwnTpwI6vMQESUH28ngYjuZOLaTsYNBIIUMRqIQ2CHAM3C5SZMmUrx4cVm+fLnb7WgMYdKkSVK5cmU1uoWAsVWrVmrKAly/fl0KFiyoek/t1q1bp0aedu/era6fOnVKnnvuOdXLlTVrVrnvvvvk999/T3B/x48fL7fddptkyJBBSpcuLcOHD483sjVjxgy1n5kyZZKKFSvKihUr3B5jzJgxUqhQIXX/I488IkOGDJGbbrpJ3Ydg7M0331T7gcfCyR6g/fvvv+pv8LclSpRQAV5CvvrqK7UPOB6exo4dq44bRsLGjRsnlmW53V+0aFEZOHCgPP300+o4Fy5cWEaPHu22Dd4fjFrieOD9wHRV++geAqvWrVurKZcZM2ZU+4xjCMWKFVPnd9xxh/qbOnXqqOvt27eXpk2byqBBg9yC/k2bNqn3CI+TI0cO9d6hA8Ewf4d9zpMnjzqmOJYYZf6///s/yZ49uzoOeK125cuXV5+hmTNnJngsiYjCge0k20m2kxQyFlEItWrVyqpXr17c9SpVqlhff/211alTJ+u1115Tt126dMnKmDGj9dlnn6nrY8eOtebMmWPt2rXLWrFihVWtWjWrQYMGcY/xyiuvWHfffbfb8+C26tWrq8vXr1+3atasaTVu3NhavXq1tWPHDnV/jhw5rGPHjqlt+vXrZ1WsWDHu70ePHm3ly5fP+uabb6zdu3er8+zZs1sTJkxQ9+/ZswdRlFW6dGnrhx9+sLZv32499thjVpEiRawrV66obX755RcrderU1vvvv6/u//TTT9VjZMuWTd1//vx5tR9ly5a1Dh06pE64DfDYBQsWtKZMmWLt3LnTeumll6wbb7wxbn+9adKkidWxY8d4t58+fdrKnDmztXnzZuvq1atWnjx5rEWLFrltg/3GvmEf8XyDBg1S+75t27a4x8D9bdq0sbZs2aLej5IlS6r9XL9+vdqmS5cu1u23366OMY7PggULrFmzZqn7fvvtN7XtwoUL1es0r6Ndu3bqdbVt21bt36ZNm6xz585Z+fPnt5o1a6au//TTT1axYsXUtgYuZ8mSRT3nH3/8oT4jePz69etb77zzjnqP33rrLStt2rTW/v373V5rixYtrPbt2/s8jkRE4cR2ku0k20kKBQaBFFIIrhCQIFBCYJEmTRrryJEj1rRp06waNWqobZYuXap+0CPo88YEFGfOnFHX161bZ6VKlcrau3evun7t2jWrQIECKqABBBFZs2a1Ll686PY4xYsXt0aNGuU1CCxUqJAKwOwQVJjA0gSBJlAFBEe4zQROLVu2tBo1auT2GK1bt44LAr09r4HH6du3b9z1s2fPqtf4448/+jy2eJwBAwZ4PeYIzoyXX35Z7YdnEIgAz0DgnDt3bmvEiBHqOs4RNF+4cCFumzFjxrgFgQiyn3rqKa/7Zo6X2dYezCEoReBv39+bb75ZvWZj9uzZKig9fPhw3N9hn/FeG6VKlbLuueeeuOsIePFZmzp1qttzduvWzapTp47X/SQiCje2k2wn7dhOUrBwOiiFFKZOnjt3Tq0BxHpATP/DFM3atWur23AfpoJiOuItt9yi/mb9+vVqymiRIkXUVEUzlXD//v1xUycwXXPq1Knq+tKlS9V00RYtWqjra9euVVMJMa3wxhtvjDvt2bNHdu3aFW8f//nnHzlw4IA888wzbtu//fbb8bavUKFC3OV8+fKpczNVFZk677rrLrftPa8nxP7YmTNnVq/dPLY3Fy5cUFM1vU0FbdOmTdx1XMY01pMnT/p8PkzZxLRJ+2vB/fbH93wtnTp1kmnTpqkpoz169HCb3psQTNFEwhpj27ZtalorXrNRs2ZNNfUX+2GULVtWUqd2fYVhWigey7jhhhvUe+55zDDF1L7+lIjISdhOsp30xHaSgiFNUB6VyIdbb71VrdVavHixWkOG4A8QcGDd2K+//qruw3owQFBYr149dcLaQKw3Q/BXv359tyQiWIs2ZcoU6dWrlzrH/Tlz5lT3IXhAgGZfi2iY9Xl22N6s56tatarbfQgs7JDZ1B442f8eA3rmNsNzLV5C7I9tHt88tjd4vZ4JT7Zu3SqrVq1SAXbPnj3jbr927ZoKmhG4+fN8/ryWBg0ayL59+2T27NmycOFCuf/++1Wm0g8++CDB12kP9nw9l32fEtpff47Z8ePH1eeIiMiJ2E6ynfTEdpKCgSOBFJZeTgRkOJlRPUBAOG/ePFm5cmVcUpg//vhDJUh59913VRkJjPh5Gw1D0hMkE8Go3/Tp01VQaFSqVEkOHz4sadKkUY2r/WQCRTuMKBUoUEAllfHc3iQ48Qf29bfffnO7zZ4ZFTAChoAsEDAiiqDPcxSwVq1aKvkMEriYE0bqcF9SXsvGjRvl0qVLPl8LILhC0hYE7EOHDo1LLmNG+vx5rWXKlFH7iA4AA50DGPULRLbYzZs3q2NFRORUbCdd2E7Gx3aSAoFBIIWlcUPJAvzQNyOBgMsYfUMpAxMEYlooGoBPPvlEBWXIkPnWW2/Fe0wEZzVq1FBTOJEhEtNHjQceeECqV6+uskkiyERmT0xV7Nu3r9dAxtQlQsbK//3vf6pWIQJMZLpEdk9/vfjiizJnzhz1Nzt37pRRo0bJjz/+6DaahaycmJaKY4Fg1x5kJRVGP5Gd1ARaV65ckS+++EKeeOIJKVeunNvp2WefVQFzYhlS7UE2RtSQpRPTNXEczQifeT1vvPGGfPfdd/Lnn3/Kli1b5IcfflDZVQFTfjENc+7cuXLkyBGVrdUXBPCYdtquXTsVsGFkGMcSmU0RoKcEpoHidWNkmYjIqdhOsp1kO0nBxiCQwtK4Yf0aRtbsP+oRBJ45c0aVi0BZBTOyhLIJX3/9ter5woigr+mFCB4Q1DRr1kwFHAaCFARjGBFDCQSMJj3++OMqGPQVVCBI+uyzz9RzYy4+9g2XkzISiHVsKF2BIBBr3BAAdevWzW1d3aOPPioPPvigOiZ4rWZdY3I0bNhQTYfEVExAwHzs2DFVZsITyjfgdfk7GoiyGt9//70KVrHmD0XpEfSBeT0I1nv37q3WDuJYY+os1ggCRmE//vhjFQijFIQ9SPeEkhgIMjFts0qVKvLYY4+pqaXDhg2TlEKQio4FjCoTETkV20m2k2wnKdhSITtM0J+FiJQOHTqoKa5IihMMqGWIQAdBVLCh6DqKyqK30h50OxmS2XTt2lWNbBIRkfOwnQwvtpOxg4lhiIIIo5Z169ZVi7oxFXTixIluRecDDdM1kRwGI6rIJhpIn3/+ucrYivWSGHFFohlkYI2UABBrSTGqiOmxRETkDGwnnYPtZGzhSCBRECFIQgIcBGUIoLC2rWPHjhF5zAcPHqwCWCTZQbZVrLF855131PRNIiKi5GA7SRQeDAKJiIiIiIhiCBPDEBERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEgVJ37595aGHHpICBQpIqlSppH379jzWREREXvz111/StWtXqV27ttx0002q3ZwwYQKPFVGQMAgkCpKPPvpIjh07Jg8//LCkS5eOx5mIiMiHP//8UyZPnqzay4YNG/I4EQVZmmA/AVGsOnPmjKROrftZvvjiixQ/3vnz5yVTpkwB2DMiIqLQqVOnjhQtWjTBkb1atWrJP//8oy6vWbNGpk6dmuLnZbtJ5BtHAili9O/fX00P2bhxozRv3lyyZcsm2bNnl+7du8vVq1dl+/bt8uCDD0qWLFlUYzN48OB4j3H69Gl59dVXpVixYqq3EVM1Mf3k3LlzbtudPHlSnnnmGfX4N954ozRq1Eh2796tnh/74Q8TAKbkta5bt04ee+wxufnmm6V48eLqPsuyZPjw4XL77bdLxowZ1X3YBvtnt379ejUdNXfu3JI+fXrJnz+/eh2YcmPgOV544QUZNWqUlCxZUm1XpkwZmTZtWrx92rx5szRp0kQ9X4YMGdTzT5w40W2bJUuWqMdE492nTx/1nFmzZpUHHnhAvT9J3T9/XysRUSyKtHYxWG2mCTTLlSsnP//8s9SoUUN1mj799NNJeo1ff/21VK1aVR1H/P0tt9wS9xj2Nm7SpEnqGOfNm1e1TZjCijbN06xZs6R69erqsfAe1K1bV1asWOH1PdyyZYs88cQT6rnz5MmjnvfUqVNJ2r+kvFYijgRSxGnRooW0adNGnn/+eVmwYIFq1K5cuSILFy6Uzp07qy+/KVOmSM+ePeXWW2+VZs2axfUI4osaQcZrr70mFSpUUF+6b7zxhmzatEn9Pb6Ir1+/Lo0bN1Y9kfhyrlSpkvrSRkMaatj3xx9/XDp27Bj3BY7Xjd7Ul156Sd577z05fvy4DBgwQDV6v//+u2o8sC0aGzQCn376qbrt8OHDsnjxYjVC6dlI4XY8RubMmVXQhYYoTZo0KuAC/JDA4yNg+/jjjyVHjhyqEcQ6xyNHjkiPHj3cHhPHt2bNmvLZZ5+pBgnvBY7ptm3b5IYbbvB7//x5rUREsS6W2sWEHDp0SB0HtEkDBw5UgaW/rxGvp2XLluqE14jOzn379smiRYviPQ8eB8cAbRwCNWyPIBSBIAIzwPFu3bq11KtXT3WMXrp0Sb0v2O6nn36Su+++2+0xH330UfXcCLSxX71791a3jxs3Tp37s3/+vlYixSKKEP369bPwkf3www/dbr/99tvV7TNmzIi77cqVK1auXLmsZs2axd02aNAgK3Xq1Nbq1avd/n769Onq7+fMmaOuz549W10fMWKE23b4e9yO/UiqzJkzW+3atUvya33jjTfcbl+xYoXXY3DgwAErY8aMVo8ePdT1NWvWqO2+/fbbBJ8H2+DvDh8+HHfb1atXrdKlS1u33npr3G2PP/64lT59emv//v1uf9+gQQMrU6ZM1smTJ9X1xYsXq8ds2LCh23ZfffWVuh377+/++ftaiYhilRPbxevXr6vnsp9q1aplPfnkk/Fu9wX7g8cdP36838eidu3a6m9++umnePvoz2v84IMP1HXTnnlj2rhKlSqp12ns3bvXSps2rfXss8+q69euXbPy589vlS9fXl02zpw5Y+XOnduqUaNGvPdw8ODBbs/VuXNnK0OGDHHP48/++ftaiYDTQSniYAqh3W233aZ6tho0aBB3G0ax0NuJXjLjhx9+UFNFMLUQ02TMqX79+urvMc0Dli5dGtezaofRMU/2x8FJx1WBg55BO7wG7Ct6Ou3PiykpFStWjHsNeO2YOole35EjR8rWrVt9Psf999/vNqKGkTr0NGKRvpmaiZ5GbFeoUCG3v8VIIHoePae3IBmOHXojwbwf/uyfv6+ViCjWOaldxLZp06Z1O2GK5ueffx7v9r179wb0OKBdue+++9xu8/c1VqlSJe41fvXVV3Lw4EGfz9OqVSu3EbUiRYqoGSqYzWJmz/z999/Stm1bt2mumEaLdn3lypWq7Uys3bx48aIcPXrU7/3z97USAYNAijhYj2CHOe+YG4+pEZ634wvUwLRFrJvwbIQwTx/B27///qu2Q0ZPNJaez+M59RCNl+djmYYyUPLly+d2Ha8B+4p98XxuNCrmNWC9APYFDQGmhJQtW1atuevXr5+aImSHoMqTuQ3Hwpx77gvgMe3bGZguaoc1f3DhwgW/98/f10pEFOuc0i7CnXfeKatXr3Y7YeokAlXP200bEije2il/XyMS03z77bcqaHryySelYMGCKqDylqDGV7tpbzN97Q9eM6bXnjhxIkntpj/75+9rJQKuCaSYkTNnTrWA28yv93a/+SLGlyzWn9kbPKxZ8/wiRyNmV6pUqYDus+fcfewjblu2bFlcA2Fnv618+fIqwQu++NEoYG0d1tPhGPTq1cvn67LfZholnGOthSf0dJr9SqrE9i8pr5WIiMLfLgICjsqVK8e7DY/heXugeVvv5u9rBCQ/wwnr99DZOGjQIDXqh6Q6SPCSWLtpbzPBV7uJ0UGMWiZVYvuXlNdKxCCQYgZ6IbFQHF/OSEjiCxZVY/H2l19+KZ06dYq73TNjJnpUg92geXsN7777rpoG4jktJ6FGEdMnUbcQgRYyjtphgTp6D02P7rVr19RrRzZS9DQCpoLOnDlTNV72nltM70Fvc7Vq1ZL9mnztX3JeKxERha9djOTX6NnJaIrWz5s3TyV8sQeBGH1DdlATdGKK7fLly9UInekQRlZOJIdBUh6zHZKiffPNN3EZQ5PL1/4l57VS7GIQSDEDKZLx5YspFd26dVPz7TElY//+/TJ//nx55ZVXVOplZDtDZktcR2ZLTG3BmjcEPElJY43pjqbmEQIrNBLTp09X1/HlnStXriS/BuzXc889J0899ZTK0obXgoye6G385Zdf1OgaGmisC0CWz6ZNm6pMZRhtmzFjhkrxjaycnj2DWEPx+uuvx2UH/eOPP9wad0zTxGPee++9KssYeoJR1Hf27NnqhwGmdyaFP/vn72slIqLIaBcTY9pIUwYI3/1YRwcmW3WwXiPaNqyDR6cnOkDRHv3vf/9T0ynRZtthnd4jjzwiHTp0UNlB0UZi6q3J6InjgbYR2UERmCFrK0bv3n//ffW46OBMKn/2z9/XSgQMAilmIIDA1EJ8+Y4ePVr27Nmjpk0ULlxY1bHDdArz5f3999+rL0tse/nyZdX4oSQCRrzQ8+YPNAr2NYJYkG0WZWPxONJEJwdq+mE/cI5ACl/wGJ3DPt51111qmxIlSqj9RCOE0TuMWqJnEiNt7dq1i7cYHWvy+vbtqxoKjAAiwENyGAN/i15OrN/r0qWLWqOAxAPjx49XyWGSyt/98+e1EhFRZLSLiUGtQzuUEMIJkpt4zd/XiOAIQScSlqEDF68Js32QGA1tpB1G27AcBJ2UCIrRHqHj1NTzBUzTxHNjyibaUyRdw7FC+48kMknlz/75+1qJIBVShPJQECXO1Pz59ddfk/UF7kSYooKgbtiwYeHeFSIiijDR2C4mBB25mBGDou3JHZkkcgqOBBJ5gfn+WIuGKYfoAcUCbEzjwBSLWGjoiIiI7NguEkUXBoFEXiCTGaZ2vP3222ohN9I8Y9ojrhMREcUatotE0YXTQYmIiIiIiGIIi8UTERERERHFEAaBREREREREMYRBIBERERERUQyJycQwqDWG2mRY5IwU+UREFBqoSnTmzBlV7zFQBaYpsNhGEhFFfzsZk0EgAsBChQqFezeIiGLWgQMHpGDBguHeDfKCbSQRUfS3kzEZBGIE0BzcrFmzhnt3iIhixunTp1UnnPkeJudhG0lEFP3tZEwGgWYKKAJABoFEROH7HibnYRtJRBT97SQXZBAREREREcUQBoFEREREREQxhEEgRa9r10SWLRM5ezbce0JERBR+Fy+KrFqFFLDh3hMiCjMGgRS9Bg0SqVULWQ5ETp4M994QERGF1yOPiFSrJnLDDSILF/LdIIphDAIpev32m+vyzTeLLF4czr0hIiIKr7lzXZfr1hWpWVPkrbf0zBkiiikMAil65cjhfv2++/Tp77+T/ljnzwdst4iIiBxh+XKRN94QSZtW5MqVcO8NEYUQg0CKPmatw9Wr+vy550Rat9aXMRpYoIDI0aP+P17z5iKZMyNXr4hlBWGHiYiIQiB9eu+3o2277TaR+fP5NhDFCAaBFD1On9aBGtY64NwEgWXLikyaJLJypWvbfPn8D+imT3ddLlEiwDtNREQUIpcu6fPVq/UMF3Sa9uun281du0Tq1xdp3JhvB1EMYBBI0WPcOPfr06bp8zRp9HnVqiKzZunLaPjM6GBiEEQaaCT79w/I7hIREYXMP/+4LmNGTMaMusMUbdqmTSJt2uj7fvhBt3VEFNUYBFL08LVuDyOEBno4M2XSl6dOFcmeXZ/OnPH9uFu2uAeTb74p8u67AdttIiKioMGsl/XrRebNc58NY4epoF984br+wQd8Q4iiHINAih4mu1mNGu63ly7tfv3AAZHU/330T5zQp86dfT9unjz6/KefXLf17i1y+XJg9puIiCgYMOulVSuRSpVE2rZNfPtbb9XnI0fy/SCKcgwCKfqCwIoV3W9H1jM7jPyhbuDMma7bsGYwscdFttENG9yn0xARETkRMmE/+KBraYQ/hgxxXeaMF6KoxiCQoodJBIMF7nnzum7HdU8oIN+0qci337puO3w44SAQj4MAs2hRff3ff/U6CiIiIifBSF6xYiILFujrAwb493f2pDCY8cKM2ERRi0EgRQ97sIbpL4aZ+plYg4c1ElOmiBw/7vtxYedO131NmgRgx4mIiAIExd87ddJLFrDWb/Zskddf10GhP3791XWZidCIohaDQIoe9mCtcmX/gkDc16CB6zoyhnoWmfcMApEgplkzfXnPngDtPBERUQqtWKGLvwPaKSQ2a9hQX69Z07/HsK+rxwgigkIWkieKOgwCKXqsW+cK0jJk8C8IhC+/1MXg7c6d8x0EwiefuC4fPJiCnSYiIgoQewCHtg0lIIwPPxS57z6dGTsxy5a5Lt99d/w2koginuOCwIMHD0qbNm0kR44ckilTJrn99ttl7dq1cfdbliX9+/eX/PnzS8aMGaVOnTqyxaTwp9h2882uoCxduoTXBHquDzx71rWm0DMT6MWL8R8nf37X5UKFUrjjREREKbRwoevyO++4yhoZuXPrtu3xxxN/LAR+c+e6rmMk0H6diCKeo4LAEydOSM2aNSVt2rTy448/ytatW+XDDz+Um266KW6bwYMHy5AhQ2TYsGGyevVqyZs3r9StW1fOJFTnjWKDyQJ6++3uQVpiI4GGPcgbPVqka1e9rsLImtV9+2ee0edYOJ8zZ/L3m4iIKKVMmwSvvZby41m/vntimOHD/fs7dMTaO1WJyJEcFQS+9957UqhQIRk/frzcddddUrRoUbn//vulePHicaOAQ4cOlT59+kizZs2kXLlyMnHiRDl//rxMQUIPim2msULvp70H1N8gEOrW1edYSP+//7nXSvIMAj/7TOTOO/XlY8f09kREROGwf78+f+65wD6uaRcXL05820WLRAoW1J2ymGFDRI7lqCBw1qxZUrlyZWnevLnkzp1b7rjjDhkzZkzc/Xv27JHDhw9LvXr14m5Lnz691K5dW5YvX+7zcS9duiSnT592O1EUwxoIexCI6Z7+6t49ac+1Zo3rMkYO//gjaX9PREQUiIQwxttvB/Z4dumizxHUmeURvowYkby2l4hiOwjcvXu3jBgxQkqUKCHz5s2Tjh07yksvvSSff/65uh8BIOTJk8ft73Dd3OfNoEGDJFu2bHEnjDZSFLJPW7FP7cQ6CH+hsK43Zcv6/ptTp1yXkY6bdZWIiCiUPvjAdTlXrsA+tskuCgn81lJKlHC/npRC9UQUu0Hg9evXpVKlSjJw4EA1Cvj8889Lhw4dVGBol8qe7eq/aaKet9n17t1bTp06FXc6cOBA0F4DOYDnZyF9+qT9/dix8W+76y7f22OaqH0qaN++SXs+IiKilJg5U5/ff3/gjyOmdprZNTt2JLzt9evu1594gh2jRA7lqCAwX758UqZMGbfbbrvtNtn/3zx3JIEBz1G/o0ePxhsdtMOU0axZs7qdKAqZETgEgUWL6h7JSpVEsmVL2uM8/TSyFLlPKU0skHzpJQxJ68sDB7rKShAREQUT2hvT/j31VHCew99EL6btK13adVu7dsHZJyKKniAQmUG3b9/udtuOHTukSJEi6nKxYsVUILhgwYK4+y9fvixLly6VGvbaOEQoEbFtm8jq1UlLDGMgI6290bv11sT/xr5ofvp0vgdEFBQspURudu50XX7sseAcHHSoehvp8xUENmniuu2LL5gtlMiBHBUEduvWTVauXKmmg/75558q4+fo0aOly3+LkjHls2vXrur+mTNnyubNm6V9+/aqnmCrVq3CvfvkpJFAsy4wOQGgN571lrzBekBj6dLAPC8RkQ1LKVE8S5Ykf/mDv0xbmtgsFxMkov21B6eoO0hEjuLHL9vQqVKligrusIZvwIABauQPJSFat24dt02PHj3kwoUL0rlzZ9UYVq1aVebPny9ZmIWKAq1pU5Fvv/U/CIRq1URWrhTJlInvBxEFtZSSgXJKhmcpJUApJSyZQMcq1tpTlEFJI7B9DgLOJFvzdyQQQSNm0GTOLHLunMiqVbp+YIECwdtHIorckUB46KGHZNOmTXLx4kXZtm2bSgxjh9HA/v37y6FDh9Q2mAqKeoFE8UYCU/5hdF32NwisU8e/hpKIyCGllFhGKcL99JM+r149eM+RnJFA+Osv132oH5hYiQkiit0gkMgx7OtM/Q3q/G0oiYgcUkqJZZQi3IUL+vzee4P3HKZtS8pIoFlfj9kxRsaMwdpDIkoiBoEUPQI9EvhfQqJ4mc4CMWWGiMghpZRYRimC2evU2mevBJq/bdvPP7tvD1WrupdZ6t49GHtIREnEIJDIF6zrGzlSpFEj/3tYORJIRBFWSolllCIYMmAb+fIF73n8bdtuuUWf//uv++1YE2h89JEuw0REYcUgkKJHoEcCAUkUfvjB/+05EkhEQcRSSuTGrPMMZLuXUPv6++8Jb2eCxNtvj3/f7t2uyzlyBHLviCgZGAQSBRJHAokoiFhKidxs2aLPK1YM7oFBZk9/gjcTBNqngxrFiqEXwxVU2mo+E1GMl4ggctxIYLAWzxMRJQNLKZGbdOn0eYkSwT0wCN7+/DPx6aDmfl8ZtbFm0ASIyGCL7QNVz5eIkoT/84gCyTRu48bpYBSnM2f0bVeuiPTqJTJ5Mo85ESUbSylRnF9+CU0xdn+XOly96r69JwR8EybEf1wiCjkGgRQ9nDASaM/UZmTNqs+7dEGlZ5E2bRJfV0FERJQYFGN30lKHhKaDGu3aiRQq5Lrep08g9pCIkohBIFEgYc2DN+++K3Ljja7rWDS/YQOPPRERJd/Wrfq8XLngHkUT1CUWBP76q/v2vvyXzVYZOJDZQonCgEEgRQ8njARmyeK6bF9A37t3/CK5zzwTuv0iIqLobfeCPSLobxBoRvjMWsWEbNvmupw9e0r2joiSgUEgUSDZez/r1xf5/HPX9enT3bddt47HnoiIUhYAQpEioWnbLlxIeDusfYcCBRJ/zNKlRRo2dF0fMCAle0hEScQgkKKHE0YC7UEgpn+2beu6vmOHPn/wQddtM2aEcOeIiChqmIALMmQI7nOZhDD24vTeXL6sz9Om9e9xZ892Xe7XT2Tv3uTuIRElEYNAokCyp8XOn1+fv/aa+zb2IrqPPioybx7fAyIiSpoTJ1yX06cP7tG7eFGf2xO6eOuIPX7c/+mgxsaNia+rJ6KAYxBI0cNpI4Hly+tzlIWwQw9ps2au6xgZ3L07RDtIRERRwQRc4LnmPNBM4hlTAsKb06ddlxMrKm+HtvKVV1zX77knOXtIREnEIJAokOw1lMz0HHuyGPjnH5FvvhFZtsx1W/HiImfP8r0gIqKkTQfNnTv4R8xM77RPQfU1FdReGslfH3zgXvvQZD0loqBhEEjRwwkjgfbF+fY1EfYpLnfe6Sru+913rttvuSXxQrxERET2UTl/198FYqnD33/73sYEiJgRY+oKJoW9IxSJ1RLLREpEKcIgkKJPOINA+zoI+340aOB9yujDD4u8/rprhPDVV0Oxl0REFOmSmoQlJUxAtnOn722OHUv6ekA7lLl46y19+a+/9AwZewZUIgooBoEUPZzQWNgbY3uKbPs6Cs8iukiLbZLIeJaRICIi8mbXrsSnaAaKWeNn2qqEEtUkVkYiIX37iowapS/v2ydSoULyH4uIEsQgkKKPU0YC7esjKlXynkHU+OQT12ggERGRv52O//4b/GNl1h36sybQJEVLrueeE8mUSV/evFlk6dKUPR4RecUgkCJ/9M9MU3HCSGC+fN4Xxic0EmhfM5gtWzD3joiIooVp+2rWDF0HZ0LTQU2Nv0CUq7CXv6hTJ+WPR0TxMAikyHX0qMgDD+iRtSNHXLeHu0TE+vUiP/zgngymZEn/GlguhCciIn+YzkVvs0sCzXReJjQSaGoJ7tmT8udDmzhsmOv6xx+n/DGJyA2DQIpM3buL5MkjsmiRvo7F5E4YCTTF4Bs1cr/N3kh7loywN7AMAomIyB+mvfA2uyTQChd2dbL6amtNgFirVmCes0sX1zTUl18W+fHHwDwuESkMAilyYN3DpUsimzaJfPSR+332QrnhHAn0xR4EInj1ZNJpMwgkIiKnjQSaurf2JRieVq3S5zfdFLjnPXhQl1OCpk1FVqwI3GMTxTgGgRQZHnpIJFcu3RB5yxaGxtApI4He2Btpb+m8TU/u6dM6iMXJrK8gIiLyhKUH9vYjVEnPzp/3vo0J/hKqJZictnPOHJFy5XTimRo1dDF5IkoxBoHkfOfOicyenfA29nUKTh8JTCgItMOaQqTIJiIi8pQ9uz7fvz/4x8Zk6zSjcwmtCQx0IhcsocDSjxtv1NfvuSc0ZTGIohyDQHK+5593Xb7zTpGpU0WuX3dvlJw+ElikiPesoYavnlysLcTUm379RHr0CN7+ERFRZDElGe69N/jPhSULJujEsgxvMGJnnzoaSJgJZE8UE4znIIoxDALJ+SZPdjUCa9aIPP64Hu3btk0kb15938KFImfOOHckEIvbn3xS5LHHvBfbxWuzmzVLn2/Zohs7FJR//32RIUNCs79ERORshw/Hn6oZTKYD86+/vN9/6636HJ20wdCuncgtt7ie4513gvM8RDGCQSA5m73HceLE+NnK2rd3NT7Ll4eucG5yYP+//tp7kGrv1XzxRZHGjUVq145fY/CVV/S6QSIiim07dsRvI4LJrFPHEg1vVq/W52XKBG8f/vzTdblvX99TU4koUQwCydnmznVdfvDB+PeXL6/P581z3YbsoZHM9Op++aX3+1u3dvbUVyIiCj4zg8S+NCKY6tZNOAg0wai3de+Bgk5Uexv/2mvBey6iKMcgkJxt5kzXZW8jaKFIjR1qFy64SkmY6a52KETfuXPId4uIiBzEJEdBErFQdlBiWYY3plSTmbIZLMgUWqWKvvz553r2DBElGYNAcjYzBbRePe/3hyI1dqjddpvr8iOPuC43bCgyaJC+PHKkSLduod83IiJyBrMOPpgjb3Znz/quA4g1eqYDMxQjk1OmuC4jYQwTpxFFVxA4aNAgSZUqlXTt2jXuNsuypH///pI/f37JmDGj1KlTR7YgeQZFH/uUxxYtoj8INEXkK1f2/rrR4Pfq5Zr+MnSoThhDRESx59dfXZk7Q6F6dX3urWD7gQOuyyaLaDAhD8CkSa7rSJyGLNpEFPlB4OrVq2X06NFSwaMw+ODBg2XIkCEybNgwtU3evHmlbt26csb0iFH0WLfOdRkZQb05eTL+bU7MDuqPJUt0PcRq1Vy3VazoPgUGkBHNdIyg0WvTJsQ7SkREYVe8uD439fOCzbS33p7vxAl9nj596EYmsT4eZTJMZzA6RSM9JwBRrAeBZ8+eldatW8uYMWPk5ptvdhsFHDp0qPTp00eaNWsm5cqVk4kTJ8r58+dlin1qgIdLly7J6dOn3U4UARYvdl3OnNn7Ntmy+S5YG2lKl9ZTPu3sNQXtabk/+si1SB8lNL79NkQ7SUREjoAasqYEUSiYWSrmee1MwXpfNQSDBQGnfTYYBg6YOI0ocoPALl26SKNGjeSBBx5wu33Pnj1y+PBhqWdbH5Y+fXqpXbu2LDflAXxMK82WLVvcqVChQkHdfwpwKmhTe8hXMfWE1tRFOvt0V8/aS9984752MFKDXyIiSjqTjTNUyyLMCOCPP4Y/SY1dqVLuheRRk5eIAh8EXrhwQQ56qcsSqHV506ZNk3Xr1qnAzRMCQMhj1k79B9fNfd707t1bTp06FXc6YJ+7Ts5l6v3dfXfC2cr27XO/7eWXJSp59m5myeI+AmgysxFR2AS7jfTEtfMxzIzIhSoING1M0aK+l28EOzOoL126uGYGYa3guHHh2Q+iaA0Cp0+fLiVLlpSGDRuqtXqrVq2Ku69t27Yp3hkEZy+//LJMmjRJMtiLZ3tAshg7TBP1vM0Oo4VZs2Z1O1EEWLQo8ZFAUzS+Zk334CgaeZuC06SJyB13uK5jvSARhUWw20hPXDsf40IdBJpRPlM03s5kBA1n8XasSzS/BZ55RuTnn8O3L0TRFgS+/fbbapTu999/l3HjxsnTTz8dtxYPgVhKrV27Vo4ePSp33nmnpEmTRp2WLl0qH3/8sbpsRgA9R/3wN56jgxQFzLRdf9Y7mCxp0cxzxNNYu9Z1uW9fkUOHQrZLRBS6NjKYa+cpAh09Gtp6ufa6tefPu9+3erU+N2vVwwGDAXPmuLKTYknRwoXh2x+iaAoCr1y5Irly5VKXK1euLD///LOMGjVKBgwYkOBInL/uv/9+2bRpk2zYsCHuhOdBQ4fLt9xyi8oGumDBgri/uXz5sgoUa9SokeLnJ4fZuFGflymT+La+6ghGgzp1dApwX8lf8H/PnhEtf/6Q7RoRha6NDNbaeSZPi+D1gPYi7sFmL/1gagIayApqzxIaLpjptXOnSPnyep1igwYiS5eGd5+IoiEIzJ07t2w0P8xFJEeOHCog27Ztm9vtyZUlSxbVa2k/Zc6cWT0PLpuagQMHDpSZM2fK5s2bpX379pIpUyZp1apVip+fHMb8aPJn+q69tl40ZklFxjUsfvcF5SM6dXJdf/HFkOwaEYWujQzW2nkmT4tAKI3gbYQumOzTTnfvdr/v+HF9XqWKhB2C1V9+0ZlCESyjI/Xrr8O9V0SRHQR+8cUXqpGzS5cunUydOlWNxoVCjx49VCDYuXNn1dOKBfjz589XASRFEWTCNNOnQtXAOZk/032GD3dth0xpLJxLFFKhaCODsXaeydMifCQwVGsC7TxHAn/7zX1tYLih8xgdqPny6evt24ucOhXuvSKK3CCwYMGCajqmNzXtiTkCaMmSJWp9g4FGrH///nLo0CG5ePGialgxSkhR3MsZqqku0XLc0PtpCueajG1EFHShaCODsXaeydMiPAgM1ZpAMO2L58h2gQL63LY+1REjglOnutYw3nRTuPeIyFEC8s2BYAxTXdDIXPeoZfbwww8H4iko1hw75rqcQG83eUBPP9YOmjTdd96p10WE8kcCEQWtjTRr5+2eeuopKV26tPTs2dNt7fwd/2UONmvn33vvPb4z0SJcI4Gmc8GzTdm2TZ8XLCiOUru2yMyZupYuYNBg8+Zw7xWRI6T4l+HcuXPlySeflH9NTTcbjNpd85bWnigx9mkbZsE5+Z/G+6OPRLp109cffVQHhgFOTEFEoW8jzdp5O/vaeTBr50uUKKFOuMy181HGfG6QNCyU3+3I/jl5sgiSDHXsGP9+J5bgatrUdRn1OmfNQu9LOPeIKDKLxXt64YUXpHnz5mp6Jno47ScGgJRsGL0CrgdMnq5dRd54Q19Gg/f00/wwEoVBONpIrp2PAWZEzmNkOeiOHNHn9qmV9vInOXOKIyG5mr2+7j//hHNviKIjCMT0lu7du7NOHwUnCOQ0xuR78009IggTJuCXYUDeGiJyVhvJtfMxyB7UhBIybcKOHa7b7J0Z4UhS4w/kFrCvkX/8cffglSgGpTgIfOyxx1QDRBRQZupU2rQ8sCkdEUQBeXj/fZGPP+bxJAohtpEU1I7SkiVDe4BNwGdGIhGM2oNAJ3fcYo2s6RhdtEjkpZfCvUdEYZXi/63Dhg1TU12WLVsm5cuXl7QeP9pf4n8ySg5TcHbPHv+2P3uWx9mXt97SU3jGjBF5+WWR0qVFbIWkiSh42EZSUIPAUHeUmiygN96oE49hdK1GDeePBNo7RjGF9pVXdCklZDvt0CHce0UUmUHglClTZN68eZIxY0Y1ImivQ4TLDAIpRQ1ctWr+bV+8OA90QkaOFNm5E/PGdJa0NWtEbruNx4woyNhGUlD8/Xd4Rt7y59fnv/7qug1JYiJhJNDo3l1nCB0/XuS550RuvVXk3nvDvVdEIZfi/619+/aVAQMGSK9evSQ1slQRBcKqVfrco/CyT07vfQw3/N9EhlD03O7aJfLAAzoQNIV0iSgo2EZSUKDuHezeHdoDnC2bq03xlpQmUtri0aNFtm7VvzUaNXIdT6IYkuKoDfWHWrZsyQCQAstkHvMoeOwTyx/413gvWKCPLXqRq1YV+fPPFL1NRJQwtpEUVJUrh/YAm45DX1lJI2Ek0OznqFH68oULTBJDMSnFQWC7du3kyy+/DMzeEHlmPkOhV39wFNr/GoI//aRrOR04oNcHzp3Lzx1RkLCNpKAWi8+ePbQHGGsBfSlcWCJK0aKuy5cvh3NPiMIixV02qHM0ePBgtS6wQoUK8RLDDBkyJKVPQbFo4cKkFYpnEOi/SpVEfvtNp/rGSGuDBrpmklPrOxFFMLaRFNQgMNSJYXLlSrgMQyTJnNl1GZ2iWBtIFENSHARu2rRJ7kDaXcE6282B2CciPWL1++8ip075dzQ4HTRpSpXSKbLLlHE17KyZRBRwbCMpKExG7HBMv8RMktOn498eacsL7MfujTd09mwskyCKESn+9li8eHFg9oTIW3bQ22/377hwJDDpkB20eXORr7/W1z/7TOTZZ/k5JAogtpEUcEhiYmZZ+VqbF0zeAkB48EGJOOhARgfo1Kn61KmTyPDh4d4roshYEzho0CAZN25cvNtx23vvvZfSh6dYldQaSBwJTJ6vvnL1fKJW0rRpyXwgIvKGbSQFZRrjsWPu00JDqXx577dnyiQRx3MGzIgRrgyoRFEuxUHgqFGjpDSSS3goW7asjERtMqKUBIH+TnXhSGDy/fKLSK1a+vITT7jXfyKiFGEbSQGF4ux24Zi+6Cs5jEnoFukw0jlwIOq76JqCLB9BUSrF00EPHz4s+bzUGsuVK5ccOnQopQ9PscpMM+ZIYPAh0J41S6RgQb3O5L77RH74QaRu3RA8OVF0YxtJAeWZjT0cyUwuXvR+e8mSEtGuXXPVOezTx3X7hAm6ru4tt4Rt14gcORJYqFAh+dXLyAFuy58/f0ofnmKV+bLlSGBoYPrL3r0YwtepsuvVE/n88xA9OVH0YhtJAZ+5YXTtKvLww6E/wNWruy5nzOi67O8afidCJyhmFHlLcHjihEjx4uGZekvk5CDw2Wefla5du8r48eNl37596oT1gN26dZMOWGNElJLpoPhi9geng6Zcjhwiy5eL1Kihr7drJzJ4cAAemCh2sY2kgEJZHxMAfvRReA6ufXqkGTkLR7mKQGjdWp8jMyigI7RZM+/b3nln6PaLKBKmg/bo0UOOHz8unTt3lsv/FdvMkCGD9OzZU3r37h2IfaRYxMQw4YHU30uXirRoITJzpkjPniInT+r1EUSUZGwjKSgB2H+lucIC6xAxRdIUiN+6NXKDwE8/1WvhH3jA/bYZM1y1ivEad+4U2bgRi3xFnn8+bLtLFEipLCswxcHOnj0r27Ztk4wZM0qJEiUkvb9FvsPg9OnTki1bNjl16pRkxY9ech6T7XPLFlctu8R6R7E2NU8eV08pJR++Fjp2FBk9Wl9Ho4esaczCSikUq9+/bCMpIMx38G+/iVSpEp6DikAI7QMgQNq/X19GdumWLSUq2Ns6tIcIEn/6SV8fO1bk6afDtmsU/U6HqJ0MWJXRG2+8UaqE6wuJost/I8oJZiHzlDevyD//+L89Jd4AoqG/6SY9JRSXEVyjkc+QgUePKInYRlKKXbjgulyoUHhrzNpHBU0QWKyYRK158/T6yzlzRJ55Rq8TfOWVcO8VUXjXBBIFtaHLndv/v8uZkwFKoKHWp6n3+d13InfdJXLwYMCfhoiIEoHpiMlpGwPNXkcvS5bIrhPoL6x9RBvYpIm+/uqrurD89evh3jOiZGMQSM4eCUyXLpx7QtCjhx4BRKbWTZv0WhRMRSIiotD53/+ckQytVCnX5ezZXZcjcU1gUqANxFp5MxUWtbDvv1/kzJlw7xlRsjAIJOfBtE7T88asn86AdR6rVuneZ7w/yCD6xRfh3isiothhRp1q1w7vfmBJwKJFemQMWaUNLB+IFpMn6/MPP4y/VALr401AvmSJXpvJGTIUgRgEkvOcPu0q3ErOUamSyIYNeiQQ782TT+o05ZwOQ0QUfD/8oM/btg3/0b73Xr1G7tIl1225cknUaNVKZ2Lt3t37/S+9JDJ3rs4eun27SOXKeqYMUQQJWGIYooBPB7VPOSFnQAbWlSt1ZjT0lKI3FIHhN9+49wgTEUWCbdt0cIXzU6dEbr5Zr30+dEjk4kU966FOHfe1b+Fy7pzzpl2amTsQbTN3MmZM+P769UVWrBCpW1cnTqtWTeTrr0UaNgzVHhKlCIPAaISGAgvI9+zRPVlItIKi60hx7ISGLNA1Aim0sE5z0iQ9MojsaKgrWK6cyKxZ4UtZTkSUFLt26fXOph6cHUoA2CFF+zvv6Hp4GP1BsHjLLSLt2ol06RKa0jn2al7hrBHoqXx5iWl4L9au1b+v/vxTpFEjkb59RQYMYEklcjwGgdEC0xBeeEGP0tgTq9jlz6+3sy/kdprVq11FWxkEOhumyaABfPRR3QuKVOFDh+ppMkRETvTXXzrj8fDhrqnsSO5Rq5aezfDHHyLDhrnW3mGE8OhRkRdfdH+c48dF1qzRSbO+/FKvk8OaOKxlDwb7GmwnlWJ47jmdMAUdgbGqSBGRdev02vkffxR5+22RX3/Vo4KcIUOxUCw+kkRdsWJMZcEPcXvwh6LppUvrHkzMWZ8+Xd/+yy8iNWuKI2HE0p5iGklIjhwJ5x6RP7Ag/pFHdAAPWCcycWJ0JQmggIm6798oFLXvEUb40FmKaZ5QvbrIBx/oKZ92qHuHdc8Itq5eFbn1VpF9+1z3I/jDD/z334+/Jhr14wL93TdmjA62DOxbtE29jAb4Of3uuyKvveZaPoFsouggJXLgdzC/RSId1mLhRzcCQAR9yOCIHkqsZ0DWKkzRQ2NleukwjcWpsJ929eqFa08oKQoU0OsiunXT1/GZw7qa2OtfIiKnwiyFZ5/VASDWm2Ma6PLl8QNAKFzYNdqGUa7163VtPPwdRgbvvFP/2P/55/h/i/WECBwDyR4AoqOUAaAzYVpw7946cypmXOF3GDoa7KU9iBzEUUHgoEGDpEqVKpIlSxbJnTu3NG3aVLYj65INBi779+8v+fPnl4wZM0qdOnVky5YtEpPwRYPpB/ixfc89ejoCGiD8APdco2DW2e3YIY6FtWV26LGlyIApUEOG6ADQ2LkznHtERKR99pmrk6p5cxH8ZsDsBX+hTT15Uk8VRWer4W1WDb73ECSillyzZrqWXEoyXaODzUAgiumn5GzInIqlNxgBxO8zZNFu2tTZnfAUkxwVBC5dulS6dOkiK1eulAULFsjVq1elXr16cs5kxBKRwYMHy5AhQ2TYsGGyevVqyZs3r9StW1fOxFqxTkxHwToGNC5IxjF/fsKZrExQ6E/xdZRo8Ai+QwJBLDRurL84OYUi8uC9M2Lt/yQROXOGSYcO+jJ+iGP9XiDX7R07pgNMTCF9/HF9GxKzjRqlpwJ26iTSpEnyH3/cONdlBKL271hyLuRgwLpA0/mAmop58+pkfUQO4aggcO7cudK+fXspW7asVKxYUcaPHy/79++Xtci89N8o4NChQ6VPnz7SrFkzKVeunEycOFHOnz8vU6ZMkZiBLxGThRFrDxAAYlF6QpDJ0TQiiXnwQd3bicxnoawBhwX74G16DkUOZM0D1E1CT7itE4eIUoYzZpIA3z0tWriuIwAMdCZPTPvDLIhChfRaaG+wTCO5pk7V58g6SZE5Q+b77/V1TEXOnFlk4cJw7xmR84JAT1gQCdn/y2a5Z88eOXz4sBodNNKnTy+1a9eW5Zjb78OlS5fUIkv7KaLhS8TA9Dt/FqGbNQRY25AQjCya6Seffy6SM6duhA4ckKDCyN+//+rLmEpDkQvrIAz0hN94o8js2eHcI6KowRkzSYDvHnsCNX9mwqQEHt8+zRRr9gFtmymqjrp6GClEByvWKSY2vdN0omHmD0Wmhx7SneoG6go+/3zg144SRUsQiFG/7t27y913361G/AABIORB5ksbXDf3+eo5RZYdcyqEHrtIhVE/A2sbsBbQH2ZEz94oeuMZICPTWatWeqH8+PESNPaRXDNqSZEJWV69NYIoMP/EEyK33aYLzRNRknHGjJ8+/dR1GUsLQjWShsDOBIT2WS2YrYMpgsh6XbGiHiXCVEF8J775pvfHMllMgdNAI9uECbpDHYmGYPRokZIl4+dCIAohxwaBL7zwgmzcuFGmmqkQNqk8pnMgYPS8za53795qVNGcDgR7VCuY6td3n9riL1Nc9qefEt7O9FZ6gx/xKJYbDL/95rrMujrRwx7soRMBvd5IrtCmjUi1ajpBAxGFdcZM1M2WwQiLPbEY6ueGCjpMsRYMM2qwBszXLAm7/v293451hkbx4gHcSQoLrBlFkr4PP9TX9+wRqVNHZMSIlCUPIoqmIPDFF1+UWbNmyeLFi6VgwYJxtyMJDHiO+h09ejTe6KAdGkDU2bCfIpK9hMInnyRtbYNZM4iaboktcgfUFsSUFZMW2yhbVi9UHzRIN6yBKgMwZ44+9yzIS5HnmWf0ea9eehTZ15QXrJPBKH/79q6pwEQU8hkzUTVbBjDSZngr4xBsGAFM6owWjBR5stcmDPRaRgqf7t1FFi92Xe/cWY8QohSIt5k0RLEQBKJBwwjgjBkzZNGiRVLM1On5D64jEETmUOPy5ctqjUSNWEgmYl/gntTyCSatdWKJXsyPcYwIli/vSottD0DxIx/FUFH/BmsNkT47pUygEKkBOrkMG6anLfftq69j2pNnplBsYz6TSKaAYszsDSUKy4yZqJotgzV3ZsYK1sv7u2QilN5+O/5tTz2lO17tzBp+TKGn6IIRQNPpbowZozvdsZaeKNaCQJSHmDRpksr0iVqB6LXE6cJ/PSNowLp27SoDBw6UmTNnyubNm1U20UyZMkkrjDhEM3tiDaSeTip7I5LQlM/ff9fnnr2Yjz0mki+f979BoGhPY50UWPOAAGDvXn39gQeS9zjkHBh1xsJ3ewIjz7WoXbrooss//qiziWJKG3pDMW0Z9S+JKGQzZqJmtgxgnZWR2MyXUJg3T2fcxhRRz+UZnvr0cb+O70i4fDmIO0hhgyncf/7p+m2FpTDogEFWbfwW4nIJiqUgcMSIEaoXEgXg8+XLF3f60rb2rUePHioQ7Ny5s1SuXFkOHjwo8+fPV0FjVENiDQNTBpIKC9INFDH1xRSTP3Ik/n34wW68/757YIrRQfzwxwJ8THWwL2hPyO23i+za5brOHs/Ygh9H6LV/6y0dPOKziSx4+LxjBJqI3HDGTAIQ9JkySBgBzJQp/J8erM1E22lvg01yEECimIcfdmUwRYfY8OH6u9Bk9cYyDIpOWOv59996ac3OnbqDFCP2yN+A2VgoNM8i8xQsVgw6deoUFrKp84iwaRO+HvRp4MDkP455jI8+8r1NnTp6myZNvN/fvLllpUplWUeO6Ot//OF6XPspfXrLmjcv4f3Ztcv9b/Cc168n//WRs334oX6fn3jC+/1//WVZbdu6Pg+pU1vWc89Z1oEDod5TCqKI+/51mE6dOlnZsmWzlixZYh06dCjudP78+bht3n33XbXNjBkzrE2bNllPPPGElS9fPuv06dPR/R7lyuX6/rh82XIUHEuzb2gbly2zrFatLGvPHsvasMF7O9qmjT4fNCjce0+h/s1nfovhhM/1mDGWde0a34cYcSpE38EMAiOtYUtJkFS8uH6Mli19b5Mtm96mb1//H7djR+8NGE4TJvj+u9atA/O6KDJcvGhZs2ZZ1vHjCW+3dq1l1arl+mykTWtZXbroIJEiXsQGGA6BY+ftNH78+Lhtrl+/bvXr18/KmzevlT59eqtWrVoqGIzq9+jMGdd3Br4/nMjs38aN8e/D95yvdvTTT8OxtxRuX31lWQULuj4HFSpY1sKF4d4rCoFQfQc7ajooeYH1e1joDk2bpixDGFLyw5o1vrcx0w58rVnwBlNDjcqVdXIZk9QHmR99ZRBdssT1XMx8Fv2QcRa1rhJLJIT1qKidhOnG+GwgpTZqfuEz1amTa/0oUQz6r/M23gnr4w2sn+/fv78cOnRILl68qJKnmeyhUQvr1u3r8JwI32vIAoppfp7MlFAiey3o7dtF3nhDL5dA4iCsFcQU44R+xxH5iUGg09lLJnjJAJckyOYJ9jV4dsePuy7XrOn/49qTfuA5sLj5++9dt/Xs6f3vzKJ9/LAn8tSwocjatSLffqvXjiIYHDlSJxLCuomEEhyFGjL7IUh96SWd0S9QpVOIKHH4/2YCP5S3MCWRnKZWLZF27bzfh+80X6I9gCffsK71zTd1Ahnz2UGG/CpVdAIZJo+hFGAQ6HRIGWxGUVLasNlTZXsrFWEP3BKou5igzZvjL2THSOFXX7lvZ892hoQyRN5ghLhJE5F16/TnE4mHUFQXiROQDOrVV/Wi+nBC+Qv07mOEEvU7MZKJ8hfI9Ifi3AheiSh4xo93XbaVkIooCZWysGc8pdhUoIBuZ5AwCG0ioJQEOghathTZsCHce0gRiEGgk9lrBn33Xcofz55509QfskNmMkhJsHnnna7LZhor4EvKzv6FFemFiSk0wSAyhq5cqWtsof4XgqsPP9QjcMhOa9Kph9ru3e5TupD5D1l2Bw7UI+rYV/TYojYiMqFylJAosPD/30CdtUiE7w3TIYoZEJ6lBIgAQR9mx/z2m+vzgk52LJ3AyUkzZMjxGAQ62RNPuC7Xr5/yx0ub1nXZVnYjjqnPVrt20h97xgy9ZrF3b9dtOXOKfPaZ6/pff+leWsxxt6f/RzFxIn9hhA0dDNOm6UYPo8qoU1mmjEiDBiLTp4e2ITSdHajVhs6ao0f1yMSjj+oA8Px53WOLqd0YIUenB9ZvYT9xHxEln70WIDqFItn8+SJXr+rZBGiPsbQC7Wq6dOHeM3IaTAfF5wWzTUwJMXSuO3U9LDlSKmSHkRhz+vRpyZYtm6pJ6NiiuHhbTI0grI2y1+RLCUwrQS0aNC5I4GJnkrN88YVImzaBeT5MO/UW5GENFX4oY4G8fcSTKDlrgd57z5VoCHLl0vU0EWxhDWEwYZ0i1rWi3pdnfU18/les0D/oFi/WDbY9QM2cWf//xgm9upjyE+Ui4vs3xkXUe4ROy59/dv1/Y5IxikXIzXDunL7cr59e0vP8867fkRRRTofoO5ifDqeaNMl1GaMcgdK2rT4/dsz99n373At4Bwq+gPAD19caDntSGaKkwg8+fF4RYM2apbOpYeoURufeeUekRAmRe+/VSZUuXAjO8UWQB4ULe//8Y0ro66/rQBDJl+bOFXn5ZV08Go3211/rThGMJN51l8hbb+mpPlj7SEQJMwEgpskxAKRYZe/sRCKZzp11IIh1hFiGgAzb9hlYRBwJdHAvJ/YLCScgkIO1Bw64fqwioUa+fK4vjf79A/985nl8jXDgx/GAAYF9PoptFy/qwAqdJ/bRQSSSQRp5ZPBEttFA98A+8oieFu0vjFpgjSOCV0yTRvIbO5TSuO8+PRX8/vv12sco+JEbUaNMMSpi3iNMqUbHDyB7YvHi4d4jovBAMjIstUkM2pSOHXVyGU4zdiyOBMYyjACYALBbt8A+tj0Jy+efiwwZomsDYiQFME000DDi4QvXA1KgIbERRrzxmcYPQ5QowWcQ/6cwAm1qDwaKmYJjSrD4C6OENWqIvPuuTgSBNbMjRujkMghYT5wQ+eYbPa0VP24xUoh1wvh/6zmSTxSLzMwWYABIsQwdhQY68tF+eCu/hRkpLVrowQCsr8fyIIpZXBPoxF5OLG5H6nvzAxN1YgIJPybti+ntME1t6FAJONRAQlp/lIv4v/9z3Y4f6nXqBP75iDw7VjDahsQxsH9/YLLS2ke5McqO/1uBgCB11Sq9FhgFplEY2B64mmmmSAiAEUhMe40QETPKFMMi4j3C/wczkoHOUnRoEsUq/H9AllAUkseaeMM+ewRZ4SdP1p2h9o5EZHV/8kndyWj/W4r672AGgU5s4Oz/aYORtwcFRzGa4M3Che49SoGErGdIg40ftMhshS8bpNfnukAKFWTrxMi3UbmyyLPP6hM6JLC+r1o1nWzCn6kyPXrojg0IZo4tZBFFUIhscMhA6lkOA4Eo1kRh/SMKUuP/F/6vOVBEBBgxLiLeI4xioAyLmQKOWrpE5A7rzbEu0N5GITkZplJjyQTaPXM7OhfRKY+RQrO+nsKCQWAUHNxkQfIKM/KHBs5eciFQUA+wcWPv9+HLIRTzxE+e1D9SGQBSKPlaU4dyJvZsuZgW3aGDSKtWOoNtYo+HEUCMBIYK6hDOmaPXE2Ldo2cAmi2bTjOPbMBYK4KGHeUp7GViwsTR378UOe9RsDtLiaIBflMi8zTaAm9JBjGbBYnTMDBgz9SOtgJJ1zA6iCUKyGRNIcMgMAoObrLYRxYwvB+M3nx7oOmJjSlFM/sPR4yojRqlgynPdar2zJw//ug9Yy62Mf8/MYW7e3cJC2RCRda31atFli3TQSE6WTyhUccIIUYK8aMAo4ZhSDTj6O9fioz36PBhV1IzTG1DKRgiShkklkFSNUwZtWcSzZhRDxy0bq0TlXHUPegYBEbBwU0W86MMQZpJOBHM57FjzT6KdvjB+PTT7muIUI6halX30fAxY0ReeEFfR0ZRNIyesA2StjhtOhqmXaNHF6ddu3Rw+OuvImfPxj8WWCOJUdAQJmhy9PcvRcZ7hB+kmNECrA1IFFgYDEDheYwQfvmlXkNvIGkZ1qI3aqQDQrQfFHAMAmOxgUOPPgpOA4btMZc7FCUo7Gss3n47eM9J5JRRBNRPsneEeJtahqmgaARRTgIL6j1hyuXp0+5/41TYP2RK/ekn7xnjkCQHoyno8cV3D2pOYdQQwTGSBuTNG/3fvxQ575H5/4qMoPhcE1Hw2o7ly/XoILJVHz3qug9rCO++WweEOGHJAQUEg8BYbOBQVB1Tz0LRu4k1RYMG6dEBLBAGjBrcckvwnpPIqcaO1clhUGAXRXUB2WyR1dZbkIf/n2b07JVXRD74QCJGs2YiM2cm7W9QoxAlMFDSAgXtK1RI9sinY79/KTLeo19+EbnnHn0Zo9xI7kREwYclEJhVgrXoc+eKbNnifj+yVKP+IGaYIHu1U2bHRKDTzA4a+Qc3yUzQhwW8/hT9DASsIcIaoUgYzSAKJnz+7R0vmA6DmoKAjKL274qRI10jahhRj6QER/ZprFh3vHmzzor60kt6Kilg7QeCXPzIxtoQz+8GJI+67TY9SooENMhMil5gzGRIpPPKsd+/FBnv0fPPi4werS+zzSIKHwwcfP+9XlePLKOm/TBLmpCQDCUrsAYd7UUY1qBHqtMMAiP/4CbJtGk6CxP8/rvuaQ8V/NjFdLBgFIonilT4gYnpLoD1gZ98otf+IeCzJ46JxB+i+L7BlFgkhzFQRxENNmCGgMkGhymvK1fqERiUqUCJl+PHfZfgKFXKFRiac1uQ7MjvX3Lj6PcIPyxROxMZC5HciYjCD8nIUNcWASHaEixv8ixjhAEHjBDed5/OWs2g0CcGgbHWwDHdNZHzoGPEBDwI9lBDc9Ei1/29eulp1dEC09HxXeQtG6qB47Bnj8imTXqt5Lp1um4heoV9BcQooYHEU2XKyOmSJSXb88876/uXnN9GeraV772ns2kTkbNguQQGFxAMzpun1xQi4ZodOiExrRtLDDClu2JF99k2Me40RwIj/+D6zT7tDGuLsMaIiMIPWUFROBcwRRujXJ5F3JFMhXTpGSTpwPRSfKdhRgMCRI8eYaTSyaZm2Drk+5ec30YaGEXAD0rAiAPWHhGR89sG/L/FbJKff9brCj2DQnTuoH1FMIgOwxdfjOmg8DSDwMg/uMkaBWS6ayJnMf8/scjdNFwYMUOiFGQIpYQdO6ZHChEcbt4sp9etk2wrVjjn+5ec30YCOhiQeMK4fFnXviSiyIJlFaauLZYYrF0rcvBg/O3+7//0NFL8v8csHLTBWHeI9epRPpX0NIPAyD+4fkHSBSyYBWQnRNIGInIOTI3ElBY7dtZEx/cvRc57ZP/Rh84YJCcioujw99969gh+B+OypwwZdPBoz6aPxGSYRYccGshgHUWdQqdD9B2cJmiPTP4xASCYjGdE5ByojeSZ/TPKeyGJHMWeAAY/EhkAEkWX/Pn1CUmfzIg/poYi8MOSAs9kZJgOjpOBABB/V6aM/l2Ny0hKhmz7JskZxcMgMJwwL9p45hn+sCRyIjQg6GVEMhRIKGkKEQVe06auy+wsJYpet96q15QjyRhG+gCXsQQDBenh3Xd1xyy2Q3IyLDfA+vytW/XJE9pvjBaiDjYu4zkQKBYu7MoAHqMYBIbT3Xe7LnMaKJFzoaFB+QPwLJBLRMHz1FOuy198wc5SomiHEUDPmTeY/ol15ajLW61a/OUZBw7othkBIZK47diht8eadHTgmk5czymmRYroYBAnBIk4IUENzmNgzT+DwHCZPNl1+a232LARORkaA9QKnDlT5Kuvwr03RLEBP/gmTHBdb9MmnHtDROFUtqz32zGah2AOJwSLdphKimAQ6w3/+ksnmNq9W+fjuHhRB4w4+SoRVbSorqNtRhHNdTyX6RiOYKksKxIrHUfBonfWBSSiGOSI71+KjPcI5VdMMgj05OMHGBFRSl25IrJ/v8i+fa5zBIcIEjGK+O+//nUOYwTRBIbmHCdkNc2XT2c0TQYmholmffu6Lk+dGs49ISIicp7ffnMFgHfeyQCQiAIHiWSKF9cnX7MQEBSaIHHXLt0RhcsYUcQI46lTIps26ZOvEUqsPcRIpENxJDDUvZyocWJPYxt7A7FEFMMcM8pEzn2P0C7aEzZcuxbzCRyIyEHOntUBItYi7t3rOkeAiEAR1/G9BS1a6Lwfvr5LsdZ5xgxd//Dmm9U01NOZMkm2fv1YIsKX4cOHy/vvvy+HDh2SsmXLytChQ+Wee+4Rxytf3nUZBTKJiIiCIGLbSdT+Ml57jQEgETnLjTfqNYq+1imiI6t1az3bD3kEFi4UqV5dJ53BYBASQ6LsxZQpIj//LOESkSOBX375pbRt21Y1cDVr1pRRo0bJZ599Jlu3bpXCmJ/r1F7OadNEnnhCX8Z+oheBiCiGhH2UKUakpJ0M63uEEhDPP+9aE4jU70REkeirr0S6dhU5dCjh7RAgtmolcuKEymh6+vBhyfbll0H/Do7IILBq1apSqVIlGTFiRNxtt912mzRt2lQGDRqU6N8HpIFbvFhH8UhNa04Y+vW8jHMsMEWkv2CB/ttcuUQOH2bvJhHFHAaBzm8nA/Yeffutqy3ETw3TPnpevnRJt4mLFrl6xfPk0T+c7EnUiIgizcWLIuPGiXz/vciFC/o2fM+hmH3z5nrEENlHbZgYxofLly/L2rVrpVevXm6316tXT5YvX+71by5duqRO9oObYt2760KVSYWRwLFjGQASEZEj2smgtJHw2GOudTFJ0aGDyKefMgAkosiXIYNI5876ZKADzAGF6iOuTuC///4r165dkzzoJbTB9cPoSfQCvZ5vvvlm4NcsYE4w3kQs5sS55wm3oxcze3Y9D7hRIx35ExEROaSdDEobCVj3gh87aAfRJvo6R7I0zJApU0bkoYdESpYM/L4QETlF6vAHgBEZBBqpPKaIYFar521G7969pTtG7my9nIVQxyMlMLRLREQU4e1kUNpIWLIk5Y9BRERBEXFBYM6cOeWGG26I15t59OjReL2eRvr06dWJiIgo2iW1nWQbSUQUe5wxHpkE6dKlkzvvvFMWmCQr/8H1GjVqhG2/iIiInIDtJBERRd1IIGDaClJfV65cWapXry6jR4+W/fv3S8eOHcO9a0RERGHHdpKIiKIuCGzZsqUcO3ZMBgwYoIrglitXTubMmSNFihQJ964RERGFHdtJIiKKujqBKYXaRzfddJMcOHCAxYqJiELIJB05efKkqkVHzsM2kogo+tvJiBwJTCmMIkJAsp8REVGyvocZBDoT20giouhvJ2MyCMyOun0iah1hJPwIMT0CkTJyyf3l8eXngf/fEhplKly4cNz3MDkP28jgirQ2MhL3mfvL4xvJn4dTIWonYzIITP1fkUYEgJHwYTCwr9xfHl9+Hvj/LRq+H8z3MDkP28jQiLT/s5G4z9xfHt9I/jykDnI7yVaYiIiIiIgohjAIJCIiIiIiiiExGQSmT59e+vXrp84jAfeXx5efB/5/4/cDsc1hGxku/B3C48vPQ/T9f4vJEhFERERERESxKiZHAomIiIiIiGIVg0AiIiIiIqIYwiCQiIiIiIgohjAIJCIiIiIiiiFRGQQOHz5cihUrJhkyZJA777xTli1bluD2S5cuVdth+1tuuUVGjhwZsn0dNGiQVKlSRbJkySK5c+eWpk2byvbt2xP8myVLlkiqVKninf7444+g72///v3jPW/evHkde3yLFi3q9Vh16dLFEcf2559/lsaNG0v+/PnV83z77bdu9yNvE4457s+YMaPUqVNHtmzZkujjfvPNN1KmTBmVWQrnM2fODPr+XrlyRXr27Cnly5eXzJkzq22efPJJ+fvvvxN8zAkTJng95hcvXgzq/kL79u3jPW+1atUceXzB23HC6f333w/58fXnu8tpn1+KvHaSbWTwsZ1kO8l2ckJMtpNRFwR++eWX0rVrV+nTp4+sX79e7rnnHmnQoIHs37/f6/Z79uyRhg0bqu2w/WuvvSYvvfSSOrihgIYVAcnKlStlwYIFcvXqValXr56cO3cu0b/FB+nQoUNxpxIlSoRkn8uWLev2vJs2bfK5bbiP7+rVq932FccYmjdv7ohji/e5YsWKMmzYMK/3Dx48WIYMGaLux2tBwF23bl05c+aMz8dcsWKFtGzZUtq2bSu///67Om/RooWsWrUqqPt7/vx5Wbdunbz++uvqfMaMGbJjxw55+OGHE33crFmzuh1vnPBjM5j7azz44INuzztnzpwEHzNcxxc8j9G4ceNUQ/Xoo4+G/Pj6893ltM8vRV47yTYy+NhOsp1kOymx2U5aUeauu+6yOnbs6HZb6dKlrV69enndvkePHup+u+eff96qVq2aFQ5Hjx5FyQ5r6dKlPrdZvHix2ubEiRNWqPXr18+qWLGi39s77fi+/PLLVvHixa3r16877tjieWfOnBl3HfuYN29e691334277eLFi1a2bNmskSNH+nycFi1aWA8++KDbbfXr17cef/zxoO6vN7/99pvabt++fT63GT9+vHpNweZtf9u1a2c1adIkSY/jpOOLfb/vvvsS3CZUx9fzu8vpn99YFsntJNvI4GM7GThsJ13YTlqOayejaiTw8uXLsnbtWhVl2+H68uXLfUbTntvXr19f1qxZo6a3hdqpU6fUefbs2RPd9o477pB8+fLJ/fffL4sXL5ZQ2blzpxq2xlSixx9/XHbv3u1zWycdX3w+Jk2aJE8//bQaPXHisfXsfT98+LDb8cOwf+3atX1+nhM65gn9TTA/zzjWN910U4LbnT17VooUKSIFCxaUhx56SI02hAqmAGOaRsmSJaVDhw5y9OjRBLd3yvE9cuSIzJ49W5555plEtw3F8fX87oqGz280ivR2km1kcLGdZDvpDdvJ6GwnoyoI/Pfff+XatWuSJ08et9txHQfZG9zubXsM2eLxQgmdRt27d5e7775bypUr53M7BCejR49WU3Ew5a5UqVIqWMF6omCrWrWqfP755zJv3jwZM2aMOn41atSQY8eOOf74Yn3VyZMn1TowJx5bT+Yzm5TPs/m7pP5NMGAufa9evaRVq1ZqmoUvpUuXVuvWZs2aJVOnTlXTL2rWrKk6G4INU+AmT54sixYtkg8//FBNxbjvvvvk0qVLjj++EydOVOsMmjVrluB2oTi+3r67Iv3zG60iuZ1kGxl8bCfZTnpiOxm97WQaiUKeozw48AmN/Hjb3tvtwfbCCy/Ixo0b5ZdffklwOwQmOBnVq1eXAwcOyAcffCC1atUK+peBgQQgeO7ixYurH6T4cDv5+I4dO1btP0YxnXhsA/V5Tu7fBBJGBzBKfP36dZWAIiFIxGJPxoIApVKlSvLJJ5/Ixx9/HNT9xJx6A1/KlStXViNmGGFLKLgK9/EFrAds3bp1omsWQnF8E/ruisTPbyyIxHaSbWTwsZ1kO+mJ7eTHUdtORtVIYM6cOeWGG26IFwljepdnxGxgAaa37dOkSSM5cuSQUHnxxRdVTz2mHmLKVlLhR14oRk48IQskgkFfz+2U47tv3z5ZuHChPPvssxFzbE3W1aR8ns3fJfVvAh0AYoEypjlgIXRCo4DepE6dWmXTCscxx0gwgsCEnjvcxxeQyRHJi5LzeQ708fX13RWpn99oF6ntJNvI4GM7yXbSH2wno6edjKogMF26dCqFtckAaeA6pix6g5Eez+3nz5+vRgTSpk0rwYbIHb0DmHqIKWlYZ5ccWOOD/5ihhmlz27Zt8/nc4T6+xvjx49W6r0aNGkXMscVnAf/R7ccP6zWQbcrX5zmhY57Q3wQ6AESAgaA7OT8Q8X9iw4YNYTnmmNaMkd+Enjucx9feW4/vOmR0C9fxTey7KxI/v7Eg0tpJtpGhw3aS7aQ/2E5GUTtpRZlp06ZZadOmtcaOHWtt3brV6tq1q5U5c2Zr79696n5kP2vbtm3c9rt377YyZcpkdevWTW2Pv8PfT58+PST726lTJ5UFaMmSJdahQ4fiTufPn4/bxnOfP/roI5U1cMeOHdbmzZvV/Xgrv/nmm6Dv7yuvvKL2Fcdt5cqV1kMPPWRlyZLFsccXrl27ZhUuXNjq2bNnvPvCfWzPnDljrV+/Xp3wPEOGDFGXTTZNZIzC52PGjBnWpk2brCeeeMLKly+fdfr06bjHwP7bs/r9+uuv1g033KD+dtu2beo8TZo06v0K5v5euXLFevjhh62CBQtaGzZscPs8X7p0yef+9u/f35o7d661a9cu9VhPPfWU2t9Vq1YFdX9xHz7Py5cvt/bs2aMyw1avXt0qUKCAI4+vcerUKfV/asSIEV4fI1TH15/vLqd9finy2km2kaHBdpLtJNvJuTHXTkZdEAiffvqpVaRIEStdunRWpUqV3MotICV87dq13bbHm3PHHXeo7YsWLerzx1Uw4IeetxPSuvva5/fee0+VOciQIYN18803W3fffbc1e/bskOxvy5Yt1YcTPwDy589vNWvWzNqyZYvPfQ338YV58+apY7p9+/Z494X72JqSFJ4n7JdJH4yyHEghnD59eqtWrVrqS8IO+2+2N77++murVKlS6n1CavdABbEJ7S8CKV+fZ/ydr/3FD1AE6fh85MqVy6pXr54KzIK9v/gSxnPhOXGcsA+4ff/+/Y48vsaoUaOsjBkzWidPnvT6GKE6vv58dznt80uR106yjQwNtpNsJ9lOFo65djLVfztJREREREREMSCq1gQSERERERFRwhgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIJCL9+/eX22+/3THHIlWqVPLtt98m+e+2b98uefPmlTNnzgRlvyLZ0aNHJVeuXHLw4MFw7woRUcRhOxn92E7GFgaBFDIjR46ULFmyyNWrV+NuO3v2rKRNm1buuecet22XLVumAqEdO3ZE9TsU6Ea1T58+0qVLF3WcPZUqVUrSpUsXliBo79696v3csGGDhEvu3Lmlbdu20q9fv7DtAxFRQthOxsd2MnTYTsYWBoEUMvfee68K+tasWeMW7GHkavXq1XL+/Pm425csWSL58+eXkiVL8h3y019//SWzZs2Sp556Kt59v/zyi1y8eFGaN28uEyZMcOwxvXz5clAfH8dm8uTJcuLEiaA+DxFRcrCdDC62k4ljOxk7GARSyGAkCoEdAjwDl5s0aSLFixeX5cuXu92OxhAmTZoklStXVqNbCBhbtWqlpizA9evXpWDBgqr31G7dunVq5Gn37t3q+qlTp+S5555TvVxZs2aV++67T37//fcE93f8+PFy2223SYYMGaR06dIyfPjweCNbM2bMUPuZKVMmqVixoqxYscLtMcaMGSOFChVS9z/yyCMyZMgQuemmm9R9CMbefPNNtR94LJzsAdq///6r/gZ/W6JECRXgJeSrr75S+4Dj4Wns2LHquGEkbNy4cWJZltv9RYsWlYEDB8rTTz+tjnPhwoVl9OjRbtvg/cGoJY4H3g9MV7WP7iGwat26tZpymTFjRrXPOIZQrFgxdX7HHXeov6lTp4663r59e2natKkMGjTILejftGmTeo/wODly5FDvHToQDPN32Oc8efKoY4pjiVHm//u//5Ps2bOr44DXale+fHn1GZo5c2aCx5KIKBzYTrKdZDtJIWMRhVCrVq2sevXqxV2vUqWK9fXXX1udOnWyXnvtNXXbpUuXrIwZM1qfffaZuj527Fhrzpw51q5du6wVK1ZY1apVsxo0aBD3GK+88op19913uz0Pbqtevbq6fP36datmzZpW48aNrdWrV1s7duxQ9+fIkcM6duyY2qZfv35WxYoV4/5+9OjRVr58+axvvvnG2r17tzrPnj27NWHCBHX/nj17EEVZpUuXtn744Qdr+/bt1mOPPWYVKVLEunLlitrml19+sVKnTm29//776v5PP/1UPUa2bNnU/efPn1f7UbZsWevQoUPqhNsAj12wYEFrypQp1s6dO62XXnrJuvHGG+P215smTZpYHTt2jHf76dOnrcyZM1ubN2+2rl69auXJk8datGiR2zbYb+wb9hHPN2jQILXv27Zti3sM3N+mTRtry5Yt6v0oWbKk2s/169erbbp06WLdfvvt6hjj+CxYsMCaNWuWuu+3335T2y5cuFC9TvM62rVrp15X27Zt1f5t2rTJOnfunJU/f36rWbNm6vpPP/1kFStWTG1r4HKWLFnUc/7xxx/qM4LHr1+/vvXOO++o9/itt96y0qZNa+3fv9/ttbZo0cJq3769z+NIRBRObCfZTrKdpFBgEEghheAKAQkCJQQWadKksY4cOWJNmzbNqlGjhtpm6dKl6gc9gj5vTEBx5swZdX3dunVWqlSprL1796rr165dswoUKKACGkAQkTVrVuvixYtuj1O8eHFr1KhRXoPAQoUKqQDMDkGFCSxNEGgCVUBwhNtM4NSyZUurUaNGbo/RunXruCDQ2/MaeJy+ffvGXT979qx6jT/++KPPY4vHGTBggNdjjuDMePnll9V+eAaBCPAMBM65c+e2RowYoa7jHEHzhQsX4rYZM2aMWxCIIPupp57yum/meJlt7cEcglIE/vb9vfnmm9VrNmbPnq2C0sOHD8f9HfYZ77VRqlQp65577om7joAXn7WpU6e6PWe3bt2sOnXqeN1PIqJwYzvJdtKO7SQFC6eDUkhh6uS5c+fUGkCsB8T0P0zRrF27troN92EqKKYj3nLLLepv1q9fr6aMFilSRE1VNFMJ9+/fHzd1AtM1p06dqq4vXbpUTRdt0aKFur527Vo1lRDTCm+88ca40549e2TXrl3x9vGff/6RAwcOyDPPPOO2/dtvvx1v+woVKsRdzpcvnzo3U1WRqfOuu+5y297zekLsj505c2b12s1je3PhwgU1VdPbVNA2bdrEXcdlTGM9efKkz+fDlE1Mm7S/Ftxvf3zP19KpUyeZNm2amjLao0cPt+m9CcEUTSSsMbZt26amteI1GzVr1lRTf7EfRtmyZSV1atdXGKaF4rGMG264Qb3nnscMU0zt60+JiJyE7STbSU9sJykY0gTlUYl8uPXWW9VarcWLF6s1ZAj+AAEH1o39+uuv6j6sBwMEhfXq1VMnrA3EejMEf/Xr13dLIoK1aFOmTJFevXqpc9yfM2dOdR+CBwRo9rWIhlmfZ4ftzXq+qlWrut2HwMIOmU3tgZP97zGgZ24zPNfiJcT+2ObxzWN7g9frmfBk69atsmrVKhVg9+zZM+72a9euqaAZgZs/z+fPa2nQoIHs27dPZs+eLQsXLpT7779fZSr94IMPEnyd9mDP13PZ9ymh/fXnmB0/flx9joiInIjtJNtJT2wnKRg4Ekhh6eVEQIaTGdUDBITz5s2TlStXxiWF+eOPP1SClHfffVeVkcCIn7fRMCQ9QTIRjPpNnz5dBYVGpUqV5PDhw5ImTRrVuNpPJlC0w4hSgQIFVFIZz+1NghN/YF9/++03t9vsmVEBI2AIyAIBI6II+jxHAWvVqqWSzyCBizlhpA73JeW1bNy4US5duuTztQCCKyRtQcA+dOjQuOQyZqTPn9dapkwZtY/oADDQOYBRv0Bki928ebM6VkRETsV20oXtZHxsJykQGARSWBo3lCzAD30zEgi4jNE3lDIwQSCmhaIB+OSTT1RQhgyZb731VrzHRHBWo0YNNYUTGSIxfdR44IEHpHr16iqbJIJMZPbEVMW+fft6DWRMXSJkrPzf//6nahUiwESmS2T39NeLL74oc+bMUX+zc+dOGTVqlPz4449uo1nIyolpqTgWCHbtQVZSYfQT2UlNoHXlyhX54osv5IknnpBy5cq5nZ599lkVMCeWIdUeZGNEDVk6MV0Tx9GM8JnX88Ybb8h3330nf/75p2zZskV++OEHlV0VMOUX0zDnzp0rR44cUdlafUEAj2mn7dq1UwEbRoZxLJHZFAF6SmAaKF43RpaJiJyK7STbSbaTFGwMAiksjRvWr2Fkzf6jHkHgmTNnVLkIlFUwI0som/D111+rni+MCPqaXojgAUFNs2bNVMBhIEhBMIYRMZRAwGjS448/roJBX0EFgqTPPvtMPTfm4mPfcDkpI4FYx4bSFQgCscYNAVC3bt3c1tU9+uij8uCDD6pjgtdq1jUmR8OGDdV0SEzFBATMx44dU2UmPKF8A16Xv6OBKKvx/fffq2AVa/5QlB5BH5jXg2C9d+/eau0gjjWmzmKNIGAU9uOPP1aBMEpB2IN0TyiJgSAT0zarVKkijz32mJpaOmzYMEkpBKnoWMCoMhGRU7GdZDvJdpKCLRWywwT9WYhI6dChg5riiqQ4wYBahgh0EEQFG4quo6gseivtQbeTIZlN165d1cgmERE5D9vJ8GI7GTuYGIYoiDBqWbduXbWoG1NBJ06c6FZ0PtAwXRPJYTCiimyigfT555+rjK1YL4kRVySaQQbWSAkAsZYUo4qYHktERM7AdtI52E7GFo4EEgURgiQkwEFQhgAKa9s6duwYkcd88ODBKoBFkh1kW8Uay3feeUdN3yQiIkoOtpNE4cEgkIiIiIiIKIYwMQwREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERDGEQSAREREREVEMYRBIREREREQUQxgEEhERERERxRAGgURERERERBI7/h9G5wqVK9TOuQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "arm_label_arf = ['heg-1 response','heg+1 response','meg-1 response','meg+1 response']\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "plot(\"arf\", 3, \"arf\", 4, \"arf\", 9, \"arf\", 10, color='red')\n",
    "\n",
    "axes = plt.gcf().axes\n",
    "for ax, arm in zip(axes,arm_label_arf):\n",
    "    ax.set_xlim(0, 20)\n",
    "    ax.set_title(arm)\n",
    "\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2292bef0",
   "metadata": {},
   "source": [
    "The event file can be viewed interactively with ds9. The following command will open ds9 in the separate window if this example is run on a local computer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "07eea964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_ = os.system(f'ds9 -cmap heat {obsid}/repro/{src_root}_repro_evt2.fits -scale log -bin factor 4 &')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cebee1bf",
   "metadata": {},
   "source": [
    "The extracted source is in a crowded field and confusion should be assessed. In other words, the dispersed spectrum of COUP 394 (green ds9 region-box if viewing the event file) intersects with many sources and other dispersed spectra.  To identify potential confusion, crisscross will be run on the observation. This requires an input list of all X-ray sources potentially in the field of view. \n",
    "\n",
    "---\n",
    "\n",
    "**Download source list for the tutorial:** For this tutorial, a source list of X-ray sources in the field was prepared from [Getman et al. (2005)](https://ui.adsabs.harvard.edu/abs/2005ApJS..160..319G/abstract). To run this tutorial locally, https://cxc.cfa.harvard.edu/ciao/threads/crisscross/full_coup_src_list.tsv needs to be downloaded (e.g. right click and select \"save as\" on the link above) and saved in the same directory as the notebook.\n",
    "\n",
    "---\n",
    "\n",
    "For other fields, users will have to produce their own list of X-ray sources in the field that might cause confusion. Most of the Chandra HETG observations with more than a few sources in the field of view have been previously observed with Chandra imaging. Running CIAO's `wavdetect` on an archival non-HETG imaging observation is a good way to produce a source list. Otherwise, users will have to use another wavelength (telescope) or identify the 0th order sources in an HETG observation by eye and manually create a list.\n",
    "\n",
    "An example of how to create a crisscross source list using wavdetect can be found on [\"ahelp crisscross\"](https://cxc.cfa.harvard.edu/ciao/ahelp/crisscross.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3f23a37",
   "metadata": {},
   "source": [
    "The required inputs for this tutorial are a source list (which will be input to crisscross as the parameter `main_list`) and the evt2 file and RA/DEC of your HETG-extracted source. `crisscross` will identify if any of the sources in the source list produce erroneous counts in the extracted source COUP 394. Depending on the number of sources in the source list and the available hardware, `crisscross` could take a few minutes to run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "79304bd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "crisscross\n",
       "          infile = 3/repro/COUP_394_repro_evt2.fits\n",
       "          outdir = cc_tutorial\n",
       "       main_list = full_coup_src_list.tsv\n",
       " subset_src_list = \n",
       "  single_src_pos = 83.79475306,-5.39575306\n",
       " single_src_root = COUP_394\n",
       "  wavdetect_file = None\n",
       "conf_table_level = confused\n",
       "  arf_ratios_dir = $ASCDS_CALIB\n",
       " max_pntsrc_dist = 8\n",
       "min_pntsrc_counts = 5\n",
       " min_spec_counts = 3\n",
       "min_spec_confuser_counts = 50\n",
       "       osip_frac = 1\n",
       "spec_confuse_limit = 0.1\n",
       "    max_arm_dist = 8\n",
       "  min_arm_counts = 50\n",
       "        arm_nsig = 6\n",
       "arm_confuse_limit = 0.1\n",
       "  meg_cutoff_low = 1\n",
       " meg_cutoff_high = 32\n",
       "  heg_cutoff_low = 1\n",
       " heg_cutoff_high = 16\n",
       "   highest_order = 3\n",
       "        min_tg_d = -0.00066\n",
       "        max_tg_d = 0.00066\n",
       "         verbose = 1\n",
       "         clobber = yes\n",
       "            mode = hl\n",
       "\n",
       "\n",
       "\n",
       "CrissCross Time Start:\n",
       "Thu Jun 18 11:43:53 2026\n",
       "\n",
       "\n",
       "This run is for observation \"3/repro/COUP_394_repro_evt2.fits\".\n",
       "\n",
       "No input wavdetect source fits table provided so running wavdetect on 3/repro/COUP_394_repro_evt2.fits with binsize=2.0, bands=broad and psfecf=0.9.\n",
       "If you wish to use other wavdetect parameters please run wavdetect and provide a wavdetect source fits table with parameter 'wavdetect_file'.\n",
       "\n",
       "The total number of X-ray field sources input is 1616. These will be assessed as potential sources of confusion for sources in 'subset_src_list' or 'single_src_pos'.\n",
       "\n",
       "total elapsed time has been 1.03 minutes."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "evt2_path = f'{obsid}/repro/{src_root}_repro_evt2.fits'\n",
    "\n",
    "crisscross(infile=evt2_path, outdir='cc_tutorial', main_list='full_coup_src_list.tsv',\n",
    "           single_src_pos=f'{src_RA},{src_DEC}', single_src_root=src_root, clobber=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c49cbe8b",
   "metadata": {},
   "source": [
    "`crisscross` has now finished and produced the confusion table for COUP 394. `dmlist` (or any fits table reader) can show the identified confusion for each arm. Here, only the most relevant columns are selected for display."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "daf6fe5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " \n",
       "--------------------------------------------------------------------------------\n",
       "Data for Table Block TABLE\n",
       "--------------------------------------------------------------------------------\n",
       " \n",
       "ROW    confuser_srcid grating_type order      confusion_type confusion_wave       wave_low             wave_high            flag\n",
       " \n",
       "     1        696 meg            1 spec           2.6126691536         1.9454580533         3.2798802538 confused  \n",
       "     2       1390 meg            1 spec           8.9880208912         8.3208097909         9.6552319914 confused  \n",
       "     3        187 meg            1 pnt            8.9045904665         8.7486201313         9.0605608017 confused  \n",
       "     4        515 meg           -1 pnt            2.6398747791         2.6172583374         2.6624912208 confused  \n",
       "     5        652 meg           -1 pnt            4.6294335817         4.6025095872         4.6563575761 confused  \n",
       "     6       1113 meg           -1 pnt           11.2665089081        11.1864092180        11.3466085981 confused  \n",
       "     7        187 meg           -1 arm            4.4522952332                3.970                5.180 confused  \n",
       "     8        187 meg           -1 arm            8.9045904665                7.290               12.750 confused  \n",
       "     9        187 meg            1 arm            2.2261476166                2.140                2.330 confused  \n",
       "    10        187 meg            1 arm            2.9681968222                2.840                3.120 confused  \n",
       "    11        187 meg            1 arm            4.4522952332                4.270                4.660 confused  \n",
       "    12        652 meg           -1 arm                     1.0               21.840               31.990 confused  \n",
       "    13        652 meg           -1 arm            2.3147167908                2.250                2.390 confused  \n",
       "    14        652 meg           -1 arm            1.5431445272                 1.50                1.590 confused  \n",
       "    15        652 meg            1 arm                     1.0               21.840               31.990 confused  \n",
       "    16        652 meg            1 arm            4.6294335817                3.980                5.770 confused  \n",
       "    17        652 meg            1 arm            2.3147167908                2.130                2.560 confused  \n",
       "    18       1113 meg           -1 arm            5.6332544540                5.380                5.930 confused  \n",
       "    19       1113 meg           -1 arm            3.7555029694                3.570                3.970 confused  \n",
       "    20       1113 meg           -1 arm            2.8166272270                2.690                2.970 confused  \n",
       "    21       1113 meg            1 arm            5.6332544540                4.960                 6.70 confused"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc_table_coup = f'cc_tutorial/output_dir_obsid_3/confusion_output_files/table_fits_data/confused_{src_root}_consolidated_obsID_3.fits'\n",
    "\n",
    "# View the sources of confusion in the COUP 394 MEG arms\n",
    "dmlist.punlearn()\n",
    "cols_to_show = 'confuser_srcid, grating_type, order, confusion_type, confusion_wave, wave_low, wave_high, flag'\n",
    "\n",
    "dmlist.infile = f'{cc_table_coup}[cols {cols_to_show}][flag=confused, order=-1,+1, grating_type=meg]'\n",
    "dmlist.opt='data'\n",
    "\n",
    "dmlist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7a20f897",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " \n",
       "--------------------------------------------------------------------------------\n",
       "Data for Table Block TABLE\n",
       "--------------------------------------------------------------------------------\n",
       " \n",
       "ROW    confuser_srcid grating_type order      confusion_type confusion_wave       wave_low             wave_high            flag\n",
       " \n",
       "     1        654 heg           -1 spec           2.2434677134         1.9098896723         2.5770457545 confused  \n",
       "     2        696 heg           -1 spec           2.5394510028         2.2058729617         2.8730290439 confused  \n",
       "     3        896 heg           -1 spec           4.0036047229         3.6700266818         4.3371827640 confused  \n",
       "     4       1070 heg           -1 spec           5.5581381601         5.2245601190         5.8917162012 confused  \n",
       "     5       1089 heg           -1 spec           5.5417734858         5.2081954447         5.8753515269 confused  \n",
       "     6       1198 heg           -1 spec           6.8990374745         6.5654594334         7.2326155156 confused  \n",
       "     7       1231 heg           -1 spec          12.7468867023        12.4133086612        13.0804647434 confused  \n",
       "     8       1390 heg           -1 spec           9.1588726939         8.8252946528         9.4924507350 confused  \n",
       "     9        225 heg            1 pnt            2.2023245108         2.1570122855         2.2476367362 confused  \n",
       "    10        571 heg           -1 pnt            1.1120539065     0.86905072783987         1.3612955569 confused  \n",
       "    11        160 heg            1 arm            1.1614327135                1.130                1.190 confused  \n",
       "    12        225 heg           -1 arm            1.1011622554                1.040                1.170 confused  \n",
       "    13        225 heg           -1 arm            2.2023245108                1.980                2.530 confused  \n",
       "    14        225 heg           -1 arm                    16.0               13.890               31.990 confused  \n",
       "    15        225 heg            1 arm            1.1011622554                1.080                1.120 confused  \n",
       "    16        225 heg            1 arm                    16.0               13.890               31.990 confused"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View the sources of confusion in the COUP 394 HEG arms\n",
    "dmlist.punlearn()\n",
    "dmlist.infile = f'{cc_table_coup}[cols {cols_to_show}][flag=confused, order=-1,+1, grating_type=heg]'\n",
    "dmlist.opt='data'\n",
    "dmlist.rows='1:50'\n",
    "\n",
    "dmlist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f78b472",
   "metadata": {},
   "source": [
    "`crisscross` identified some confusion (flag column 'confused'). The 'wave_low' and 'wave_high' columns indicate the wavelength range recommended to be ignored due to the likelihood of HETG confusion by source 'confuser_srcid'. The 'confusion_type' column shows which type of confusion (point source, spectral intersection, arm confusion, or read-out streak confusion) has been identified. For more information on each of these types of confusion, see [\"ahelp crisscross\"](https://cxc.cfa.harvard.edu/ciao/ahelp/crisscross.html). \n",
    "\n",
    "Next, the confused portions of the spectrum and responses are cleaned using the crisscross helper CIAO function `clean_spec`. \n",
    "\n",
    "---\n",
    "\n",
    "**NOTE**: `clean_spec` removes ALL counts in the confused regions and not just counts from the confusing source. However, `crisscross` has many tunable parameters to allow some level of potential confusion through based on the signal-to-noise ratio of the HETG source events compared to the confused events in the confused bandpass. If crisscross is unnecessarily removing counts it can be re-run with lower confusion threshold parameters. See [\"ahelp crisscross\"](https://cxc.cfa.harvard.edu/ciao/ahelp/crisscross.html) for more info.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f23a851",
   "metadata": {},
   "source": [
    "`clean_spec` will attempt to identify the relevant response files when provided with an HETG PHA2 file. This is important because `clean_spec` also zeros out the ARF for each region with confusion. The `clean_spec` tool creates a new 'cleaned' PHA2 file and associated ARFs and does not modify the original files. In this example, only 4 ARFs and spectra are cleaned because only 4 response files were created when running `chandra_repro` above (heg-1,+1, meg-1,+1). Even though only four orders have been cleaned, the new PHA2 file still contains the other 8 uncleaned (original) orders."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0fd03519",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "clean_spec\n",
       "          infile = 3/repro/COUP_394_repro_pha2.fits\n",
       "       conf_file = cc_tutorial/output_dir_obsid_3/confusion_output_files/table_fits_data/confused_COUP_394_consolidated_obsID_3.fits\n",
       "       spec_root = COUP_394\n",
       "        arf_file = \n",
       "        resp_dir = \n",
       "         verbose = 1\n",
       "         clobber = yes\n",
       "            mode = hl\n",
       "\n",
       "Warning, no ARF response files provided in parameter arf_file. Attempting to find them.\n",
       "\n",
       "WARNING-- The identified number of ARFs [4] does not match the number of PHA spectra [12] in the PHA2 file. Only the responses found will be included.\n",
       "\n",
       "WARNING-- The output 'cleaned' PHA2 file will include all original orders but only those with matching ARFs will be cleaned."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_spec(infile=original_pha2, conf_file=cc_table_coup, \n",
    "           spec_root=src_root, arf_file=None, resp_dir=None, clobber=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71b3536f",
   "metadata": {},
   "source": [
    "`clean_spec` produced a new PHA2 file and four new ARF files. They are loaded in Sherpa starting with ID 13 to avoid overwriting the previously loaded (uncleaned) spectra. `load_gratings_pha2` will find the responses again and load the new cleaned ARFs and the original RMFs. RMF files do not have to be changed because of confusion and thus the same RMF files are used for original and cleaned spectra.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5c748327",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "WARNING-- The identified number of ARFs [4] does not match the number of PHA spectra [12] in the PHA2 file. Only the responses found will be included.\n",
      "\n",
      "\n",
      "WARNING-- The identified number of RMFs [4] does not match the number of PHA spectra [12] in the PHA2 file. Only the responses found will be included.\n",
      "\n",
      "read background_up into a dataset from file COUP_394_obsid_3_cleaned.pha2\n",
      "read background_down into a dataset from file COUP_394_obsid_3_cleaned.pha2\n",
      "Multiple data sets have been input: 13-24\n"
     ]
    }
   ],
   "source": [
    "cleaned_pha2 = f'{src_root}_obsid_{obsid}_cleaned.pha2'\n",
    "load_gratings_pha2(pha2_file=cleaned_pha2, rmf_dir=f'{obsid}/repro/tg',\n",
    "                   use_errors=True, dataset_id_start=13)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "510877e9",
   "metadata": {},
   "source": [
    "Now that cleaned spectra and responses have been prepared, a plot can compare the clean spectra to the original files that included confusion. This will demonstrate what `crisscross` and `clean_spec` have done."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2c9bebde",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataset 15: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 16: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 21: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 22: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 15: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 16: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 21: 1:41.96 Wavelength (Angstrom) (unchanged)\n",
      "dataset 22: 1:41.96 Wavelength (Angstrom) (unchanged)\n"
     ]
    },
    {
     "data": {
      "image/png": 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wfDgea8aMMTRRYTJCzCFx8KBhOVo30eUUU4JYqllT5PhxNO0ZBschRSn+buwT+0YL7c8/xzy/aJJCi2bevIZjQ8stmqSCggzTqLhAkyZNVMZWSJIkidlUILoBAwbIl19+qbqxYjzkwYMH5cmTJ1K3bl2ZM2eOrF27VpImTeqWj1Nsby1ei+Gr+EihJzDeKuQ8qltX5KefRBYuNH8NWjzR1RTZWtGyh2GyaDlE8h1bc1LG9W9Grqb58w0fHzRy799v+Fjh44W3fvduw/yQpr76ynCukF0W+Z7OnjXMQLN1q6FXNBERvVgSRJN2lCMiIiIiIiJS2CJJREREREREDmEgSURERERERA5hIElEREREREQOYSBJREREREREDmEgSURERERERA5hIElEREREREQOYSBJREREREREDmEgSeThBg8erCY5v40Ztj0EJlDHpOtFixYVPz8/yZ8/v7sPiYiIEglPrBdfZMCAAdKsWTPJlSuXOvYuXbq4+5CI4oyBJBE5bO7cuXLs2DGpUqWKFCpUiGeQiIgoFmPGjJE7d+7I//73PwkMDOS5Ip+Q1N0HQETeZ82aNaolEnCF9ejRo+4+JCIiIre0js6ePVsuXLgQa7mHDx8a601cjCXyBWyRJPISN2/elA4dOki6dOkkW7Zs8u6770poaKhxvaZpMnHiRClXrpykSJFCMmTIIK1bt5Zz586ZbQflhg4dKvny5ZPkyZNLpUqVZN26dVKvXj11s4deGRIREbmLJ9WLL8J6k3wRfw0SeYlWrVpJkSJFZMmSJfLll1/Kb7/9Jn379jWuf++996RPnz7y6quvyrJly1Tlie6nNWrUUJWtrn///urWuHFj+euvv6Rnz57SrVs3OXXqlJv+MiIiIsexXiRyL3ZtJfISXbt2lc8++0w9RrB45swZmTlzpsyYMUN27dol06ZNk1GjRkm/fv2Mr6ldu7YKPkePHi0jRoyQe/fuqcft2rWTKVOmGMuVKlVKqlevrsoSERF5A3fUixEREWbPo6KirC739/dXSXWIfBkDSSIvgQH6psqUKSPh4eESEhIif//9t6qw3nrrLbPKLHv27FK2bFnZtGmTer5z5055+vSptG3b1mxb1apVi5F5NTIyUnX3Me2Ww645RESUWOtFCAgIsHoslstnzZrFzKzk8xhIEnmJTJkymT1PliyZun/y5InquoqgD2NErClYsKC6R8Y4sFbOchmysV68eNH4fNCgQSqpABERUWKsF2HPnj1mz6dOnaqC1uXLl5stL1CggMN/D5G3YSBJ5AMyZ86srrxu2bLFWJGa0pfpla7pmEndjRs3zK6+rlixQl2l1eXMmTOejp6IiMjz60VAIh5TCCIxnYflcqLEgIEkkQ/AFBzDhw+Xq1evxuieY6pq1aqq8ly0aJG0bNnSuBxde9D6aFphli5dOt6Pm4iIyFvqRSIyx0CSyAfUrFlTevToIe+8847s3btX6tSpI6lSpZLr16/L1q1bVVD4/vvvS8aMGVXSgWHDhqk06C1atJArV67It99+Kzly5LB7DOTx48fVTb9iGxYWJosXL1bPS5QooW5ERESJpV58kaCgILl165YxBwGCVL3erFu3rmTJksUl+yFKSAwkiXwEss0hOQDuMfUHMsmhOyoq0ypVqhjLDRkyRFWmkydPVskAihUrJpMmTVJTgqRPn96uff3++++qkjXVpk0bdc+xlERElNjqxRdB3YhgUodkP3rCn40bN7psvkqihJREM03LSESJ0vnz51XFiYru66+/dvfhEBERuRXrRaIXYyBJlMgcOnRIFixYIDVq1JC0adPKyZMn5ccff5QHDx7I0aNHbWa4IyIi8kWsF4mcw66tRIkMuu9gvAgmbL5//76kS5dOdalB1x4GkURElNiwXiRyDlskiYiIiIiIyCGuSUVFREREREREiQYDSSIiIiIiInIIA0kiIiIiIiJyCJPtOAlzEV27dk3SpEkjSZIkcXYzRETkIMxa9fDhQzUfnKsmCyfXYz1JROTb9SQDSSchiMyTJ49r3w0iIrLb5cuXJXfu3DxjHor1JBGRb9eTDCSdhJZI/Q3CXHxERJQwMOcpLuTp38PkmVhPEhH5dj3JQNJJendWBJEMJImIEh6HFXg21pNERL5dT3JwCRERERERETmEgSQRERERERE5hIEkebcHD0S2bkV6QHcfCRERUaL15O4T2fzLIXke9tzdh0JECYRjJMm7vfmmyN9/i8yYIfLuu+4+GvLA9NcRERESGRnp7kMhBwUEBIi/vz/PG5GX6Fd7j0w+Xke+/XOTfLOhnrsPh+zEetI7+fv7S9KkSd2eKyCJhk+Qg+7cuSPffPONbNy4UUJCQtRcUabu3r0riSEbUrp06SQ0NJTJdtxJ/w9Uo4bItm1uPRTyLM+ePZPr169LWFiYuw+FnIDKESnLU6dO7XHfv6wD7ePu94ncUx0HyDN5pgXy9HsB1pPeLWXKlJIjRw4JDAx02/evUy2Sb731lpw9e1a6du0q2bJlc3s0TERkChe3zp8/r67YYTJefMnye8p74PrmrVu35MqVK/LSSy95XMsk60Ai26I4asorsJ707jry2bNnqp7Ebx3Uk35+7hmt6FQguXXrVnUrW7as64+IiCiO8AWLShJzKOGKHXmfLFmyyIULF+T58+ceF0iyDiQib8d60rulSJFCDQG5ePGiei+TJ0/uluNwKnwtVqyYPHnyxPVHQ0TkQu66Qkdx58ktyKwDichXsJ70Xn4e8BvHqSOYOHGi9O/fX4KCgtRYEfTDNb0RERH5KtaBRERETnZtTZ8+vRq8+corr8Tos4uryMyQSEREvop1IBERkZMtkm+++aZKXvHbb7/Jv//+Kxs2bFA3ZHHFPREReSZksW3VqpXK4oYLf/fv33fLcQwePFjKlSsn3siVdSBaNwsUKKDGt1SsWFG2bNkSa3n0BEI5lC9YsKBMnjzZbP2xY8fU+5s/f371/o4dO9ap/eLCMN4jJKvCWJx69eqpbRMR+TrWk/HcInn06FE5cOCAFC1a1JmXExGRm/z6668qaNi+fbtkzpxZpQcn99SBixYtkj59+qigrmbNmjJlyhRp0qSJHD9+XPLmzRujPLLzNW3aVLp37y7z5s2Tbdu2yQcffKASEyF41H8AIcBs06aN9O3b1+n9/vjjjzJ69GiZPXu2FClSRH744Qdp0KCBnDx5UtKkSROnv5uIyJOxnoznFslKlSrJ5cuXnXkpERG5EaZuKl68uJQqVUqyZ8/u0UltPJWr6kAEaphGq1u3buo9QeshMg1PmjTJanm0PiLQQzmUx+veffdd+emnn4xlKleuLCNHjpT27dtLsmTJnNovWiOxDLkQWrZsqT4r+GGFIBWtsEREvoz1ZDwHkh999JH07t1bXanct2+fHD582OxGRORxNE3k8WP33LBvO2HakhEjRkjhwoVVIIDAYciQIWrdkSNH1Nh0dDXMlCmT9OjRQx49emR8bZcuXeSNN95QgQUmKUaZXr16qSk0AN0TR40aJZs3b1YBJJ4DHi9btizGOEB8xwNSi3/44Ydqm+gKiW6Tw4YNM5bFmHkcS9asWVWXWRzjoUOHzLY3fPhwNe8wWrMQxISHh4u3ckUdiHOK1zZs2NBsOZ6jtdiaHTt2xCjfqFEj2bt3r/E9dsV+0fJ548YNszL4LNatW9fmscHTp0+ZfI/Im7mrnnSgjgTWk17etbVdu3bqHldCdfghwmQ7ROSxwsJEUqd2z74R7KVKZVfRr776SqZNmyZjxoyRWrVqyfXr1+XEiROqNahx48ZSrVo12bNnj4SEhKgWJQR4esAHGKeHgA/3Z86cUd/XGIuI7pBLly6VL7/8UnXNxGOM87PHuHHjZPny5fL777+rwBatcXqLHL73X3vtNcmYMaOsWrVKdZVFV8n69evLqVOn1HK8btCgQTJhwgSpXbu2zJ07V20TXTC9kSvqwNu3b6tyCK5N4TmCOGuw3Fr5iIgItT28767Yr35vrQzmLLMFFxe+/fbbFx4DEXkod9WTDtSRwHrSywNJXK0kIiLXevjwofz8888yfvx46dy5s1pWqFAhFVAiuMT8vXPmzJFU/1W4KPf666+rFkz9R3+GDBnUcn9/fzXfIYI8JIRBIImgLmXKlCqARLdWe126dEleeukldRwIlPLly2dch4AVLaUIbPWulGgRRQvn4sWLVUslukki6ELgCxhvt379eq9tlXRlHWjZtVgPRh0pb225K/br6LHhx12/fv2MzzEdGLrMEhG5CutJHwgkTX9EEBF5hZQpDVc93bVvOwQHB6vugWjNs7aubNmyxiASkCgFXXyQAEUPJEuWLKmCSB1aqRDoxQW6zCLRCpLLoFW0WbNmxm6P6CaJ7rXoRmsKQS/GmejH3rNnT7P11atXV0GoN3JFHYhER3ifLFsfEZBbtgTqEPxbK580adIY5z8u+9UvMqCMaStnbMcGuJBga1wmEXkBd9WTdtaRwHrSBwJJwA8EXGXGG4orlBiwjzEjuHpORORx0JLiQNcZd8DYR1tiaw0yXR4QEBBjHYLN2OjdMk2ZjrmrUKGCaoVbvXq1akls27atvPrqq6rFEdtGsLFp06YY28U4S18V1zoQrcKYdmPdunXSokUL43I8b968udXXIPhesWKF2bK1a9eq5D+W73tc9otpQRBMYln58uWNYysx9Qhav4nIR7GejOXUsJ50WbKdNWvWSIkSJWT37t1SpkwZldFt165d6ko4Kh4iInIcuo8imERXVEv4zj148KA8RmKC/2D6Bz8/PzU9Q1xg+giMxdSdPn1ajck0hSQ6GBuILraYPmLJkiVy9+5dFWSi5QqtYkgQZHpD6xcgyNq5c6fZ9iyfexNX1YHoBjp9+nSZOXOmCkgxXQe6Eeutt+gq+vbbbxvLYznGKOJ1KI/XzZgxQz799FNjGQR8+JzghsdXr15VjzFe1t794gcTpgcZOnSo/Pnnn2pMLVql0S26Y8eOLjqLRESOYz3pAy2SSNaAigdZ+CyXf/HFF6oLFBEROQYZUfEd+vnnn6uWI3RdvXXrlpoI/s0331QJazB2EhPFYzmyh3bq1CnW7ob2QJZVjKtEIh+0MOIYTFu4kPgHrY5I2oPA9Y8//lAtVmhxRMskWsqQLRatVej+eu3aNZV4B8vQWoaWOhw3HmOc5fz589Xf5K3JdlxVByIwv3Pnjnz33XcqkEdAivOmd53FMgR4OrQUYj32jcRFOXPmVEmL9DkkAedeb0XUx6vihoyreqvxi/YL+AyiezLmqbx3755UrVpVtX5yDkkicifWkx5Gc0KyZMm0U6dOxVh+8uRJtS4xCA0NRT8wdU9uZEgarWk1avBtIKMnT55ox48fV/feJjIyUvvhhx+0fPnyaQEBAVrevHm1oUOHqnWHDx/WXn75ZS158uRaxowZte7du2sPHz40vrZz585a8+bNzbbXu3dvrW7dujafw9WrV7WGDRtqqVKl0l566SVt1apVWrp06bRZs2ap9VOnTtXKlSun1qdNm1arX7++tn//fuPrHzx4oH300Udazpw51THnyZNHe/PNN7VLly4ZywwZMkTLnDmzljp1anWcn3/+uVa2bFmn3kN3f/+yDrSPu98nck917C/Peeq9AOvJaKwnnZcE/zgafCILGyY0btOmjdlypHhHFxvTK6i+CtnokOYe86ehyxe5iT42rEYN9PPj20AKsoFiTB9acHD1knzrPXT39y/rQPu4+30i91TH/hIhEZrTKTgogbCe9H7hHlBPOvU/HWnkkdL93LlzUqNGDTWeYuvWrapb0yeffOL6oyQiIvIQrAOJiIicDCQHDhyoxkmMGjVKJQMAjNXAuJ2PP/6Y55WIiHwW60AiIiInAsmIiAiVKKFDhw5qwD8mBgUOwCciIl/HOpCIiMjJ6T+Q4v39999Xk2brASSDSCIiSgxYBxIREcVhHkmkAT9w4IAzLyUiIvJqrAOJiIicHCOJeaWQVOfKlStSsWJFSZUqldl6TNBMRETki1gHEhERORlIYjJjME2sg8ytmEkE95GRkTy3RETkk1gHEhERORlIYs4SIiKixIh1IBERkZOB5MWLF9X8kUg6YJnNbvv27ZIvXz6eW4p/169HP370iGeciBIE60AiIiInk+28/PLLcvfu3RjLQ0ND1TqiBFGlSvTjw4d50smnXbhwQQ0dOHjwoHiD/Pnzy9ixY8UXsQ4kIvI8rCe9JJDUx0JaunPnTozEO0Tx5soVnlwiSnCsA4mIiBzs2tqyZUt1jyCyS5cukixZMuM6JNg5fPiw6vJKRETka1gHEhEROdkimS5dOnXD1dg0adIYn+OWPXt26dGjh8ybN8+RTRIRJQhNE3n82D037NteUVFRMmLECClcuLC6WJc3b14ZMmSI1bLHjx+Xpk2bSurUqSVbtmzSqVMnuX37tnH9P//8I7Vq1ZL06dNLpkyZpFmzZnL27NkY3YCWLl2qumumTJlSypYtKzt27DDbD8a+16lTR1KkSCF58uRRGbsf4w/7T0hIiLz++utqfYECBWT+/Pnii1gHEpEvc1c96UgdCawnPYjmhMGDB2uPHj3SErPQ0FB87NU9uYnhuyf6RvSfJ0+eaMePH1f3OnxlWX5kEurmyNfl559/rmXIkEGbPXu2dubMGW3Lli3atGnTtPPnz6vvnAMHDqhy165d0zJnzqx99dVXWnBwsLZ//36tQYMG2ssvv2zc1uLFi7UlS5Zop06dUq97/fXXtdKlS2uRkZFqvb7NYsWKaX///bd28uRJrXXr1lq+fPm058+fqzKHDx/WUqdOrY0ZM0ZtZ9u2bVr58uW1Ll26GPfTpEkTrVSpUtr27du1vXv3ajVq1NBSpEihXuPK99BTvn9ZB9rH3e8TJSz9+85fDN8d5Nk8qZ50NKRgPek59aRTv77DwsK0x48fG59fuHBB/WBYs2aNw9uaMGGClj9/fi1ZsmRahQoVtM2bN8daftOmTaocyhcoUECbNGmS2fqjR49qLVu2VD+EcAJt/ZBxdL+WWEF6AAaS5AUVpCOV5IMHD9R3EgJHS5aB5MCBA7WGDRualbl8+bIqg4DQmpCQELX+yJEjZtucPn26scyxY8fUMgSn0KlTJ61Hjx5m20Fw6+fnp84v9oXyO3fuNK7Ha2P7/vWWCjIh6kBf5u73iRIWA0nv4q2BJOtJz6onnUq207x5c5kzZ456fP/+falSpYqMGjVKLZ80aZLd21m0aJH06dNH+vfvLwcOHJDatWtLkyZN5NKlSzbn7kI3LpRD+a+//lp1sVqyZImxTFhYmBQsWFCGDx+uutu6Yr9E5P1SpjTMEuOOG/Ztj+DgYHn69KnUr1//hWX37dsnGzduVN1a9VuxYsXUOr37Ku47duyovhPTpk2rup2C5XddmTJljI9z5Mhh7K6q72f27Nlm+2nUqJHqWoTvZBwzpoKqVKmScRs4DnSn9VWuqgPJTSIjRTZuFLGSfT4uru69LgcXnRRvcWrNeTm74aLZsmv7b8ih31/8Nzy5+0Q2/3JILu+6JgcWnDBbFylJZevEwxJ+P1w9v7LnurHMmX8vSvDf0d3rXeHIklPqOMh760l760hgPekD80ju379fxowZox4vXrxYBWwIyBDQffPNN/L+++/btZ3Ro0dL165dpVu3buo5UsWvWbNGVcTDhg2LUX7y5MlqvJCeUr548eKyd+9e+emnn6RVq1ZqWeXKldUNvvzyS5fsl4i8HxJNe3pSaYwxtBcCOYxLxHhKS3owiPUY0zht2jTJmTOnek2pUqXk2bNnZuUDAgKMj/WM3Cir37/33nvqop0lfB+fPGn40Wktk7evclUdSG4yYYJI794iVauK7Nzpss1WrOovN6OKyrEUZ6TE/wqLJwu9FCpFGxcQf4mQh3eeSIqMhu+e8pX8JUQrKsdTnpXizQrZfP1H1ffKjFO1/3uWUw4FnBKRIsb1tXuVke6/bJapwXWkQtWkcksrJgf8Tkql9oVUoHnnzD3JWChDnP+O85svS5nWRSSdhMq9SE2S+CWe76H4wHqS9aSjnGqRRKsfku3A2rVrVSY7Pz8/qVatmpqo2R74IYMr3Q0bNjRbjudI7GANEkBYlseVcQSTz58/j7f9AloJHjx4YHYjInKll156SQWT//777wvLVqhQQY4dO6bma0RiHtMbpmHCdEy4cjtgwADVwokLb/fu3XP4mPT9WO4Dt8DAQLXdiIgI9T2sQ3CJljpf5Yo6kNxo+XLD/a5dLt3szais6v7gmpvi6e5eMPyGQVD34Noj4/IQLYu6P7Q29r8hOog02LsyZvlpJ+qo+1v/bXPbkhtqf2rZKce/i6w5udmw31BJJ1qUgxlbyCuxnvSBQBI/IJYtWyaXL19WLXl6UIauUOg+ZQ9kFsSUIcg0aArPb9y4YfU1WG6tPH7EmGYqdPV+AS2VpllqcZWfiMiVkidPLl988YV8/vnnquskuqbu3LlTZsyYEaNsr1695O7du9KhQwfZvXu3nDt3TgU17777rvqOy5Ahg8rUOnXqVDlz5oxs2LBB+vXr5/Ax4XhwEQ/7O3jwoJw+fVqWL18uH330kVpftGhRady4sXTv3l127dqlLtSht4cjravexhV1IBEROY71pA8Ekui68+mnn6or4VWrVpXq1aur5fgRU758eYe2ZdkdytZEz7GVt7bc1fv96quvJDQ01HjDDwgiIlcbOHCgfPLJJ+p7Fq197dq1M45XNIWuqtu2bVNBI3pmoMtq79691YUutI7htnDhQhXYYV3fvn1l5MiRDh8Pxk8GBQWpABLjyfEdj2PUu8/CrFmz1MW1unXrqtY5TAWVNauhdcYXubIOJCIix7Ce9CDOZum5fv26Sjevp5GHXbt2GTP9vcjTp081f39/benSpWbLP/74Y61OnTpWX1O7dm213hRenzRpUu3Zs2cxyiNzq2XWQGf2aw2z0XkAZm0lJzKZkXfwhGx08VkHxlfmcn3al+LFi2uBgYHq3rK+07OaW94++OADY5nOnTvHWF+1alWH/jZPeJ+sql8/XqaN0jc5/4Otmqc7F3TJeLw3joQYl+vLFny0zaHqd0aXzVazcZqWHd9mk/HxiVVnXfJ3rP5+j3Gbkc+j/y/Si7Ge9H5PPKCedKpFEpBcAFdecdVbh8x1etbAF8HYmooVK8q6devMluN5jRo1rL4GV30ty+MKMLIFmiaLcPV+iYiIXFkHxlfmcnRDRit2p06d5NChQ+q+bdu2qtuxbs+ePXL9+nXjTa8P27RpY7Y/dFk2Lbdq1Sp+CIiIKG5ZW1u0aGG1GyiWoe8yxo8g5TzGzsQG43VQySEQRJCIsTyoQHv27GnsTnr16lVjmnUsHz9+vHodxuOgwsTYoQULFpgl0zl+/LjxMV6PcT1IWY/jsme/RERE8V0Hxkfmcqxr0KCBqj/1ehRdk7FcryuzZDEkP9FhuqxChQqprsmmkiVLZnMaLSIiIqdaJDEGB4kbkAJdr0xxdRTLkPgGV1nLli2rxu/EBldNUbl99913Uq5cOdm8ebO64pkvXz61HldATa/MYg40rN+0aZMq//3338u4ceOMFShcu3ZNXSXGDa9HBYvHekVtz36JiIjisw6Mr8zltsrY2iaOY968eSpJk2VwjLoWY12LFCmiLt5aG6tritnNiYgSF6daJHGFEldb0Tqod+vBXGNI9ICU6EjwgNY9ZPvbunVrrNv64IMP1M0aTIJtCVdMUXnbguQHegIeZ/dLREQUn3VgfGQuRwIkW2VsbRPZZzFVS5cuXcyWo4sturriAiu61CK5xSuvvKKCX7RUWoNW1G+//dbqOiIi8j1OtUiiOynGdZiODcFjpINHN1Fc1fzwww/l6NGjrjxWIiKH2HNRiTyTJ793rqwD4yNzuSPbxN+CoBFZgE2h585rr72mMv6+/vrrsnr1ajl16pSsXLnS5rExuzmR9/Hk71ry/PfOqUASVz9PnDgRYzmW4QorYJyIo1NyEBG5gp58CxPHk3dCl0vw9/cXT+OKOjBz5szqb7NsKUT3UcsWRdOWUGvlkyZNquYMja2MtW1evHhR1q9fbzb0wxa0dqJ1EtPA2IKWSsyjaXojIs/EetL7hf33G8fehKMe07UViWqQIAAZ4ypXrqwqS0yIPXToUHn77bdVGQzuL1mypKuPl4johfADPX369MYxXSlTpuSFLS+CbqK3bt1S7xuCJE/jijrQNIM4kvfo8Lx58+ZWX4PkcCtWrIg1c7me3RzzhpqWsZaVHPN/YgwkWh5f5M6dO2r+ZNP5Q4nIe7Ge9O6WyLCwMPUbB7913HnB1akaesyYMerq5o8//ig3b95Uy/AcFRfGhAAG+yN1OBGRO+jZJl+UIIQ8E7qKIkOpJ/ZscVUdGB+ZyzFOs06dOjJixAgVkP7111+q1dFyrCaCdQSSnTt3jhGsP3r0SAYPHqwS2SFwvHDhggqa0YpqGvQSkXdjPend0qdP7/bM2k4Fkoh8Me8Vbg8ePFDLLLuw4AcAEZG7IADBj2C0uOgZLcl7oMXOdAyiJ3FVHYhxiGjpQwZxZBnHeER7MpcjYJ0wYYIa12iZuRwtj0j2M2DAAJUgB9N6IIts1apVzfaN4BLbRrZWa3/fkSNHVACLRDz4f/Tyyy+r7SCZEBH5BtaT3isgIMAjhn7Euc8Qx0AQkSfDF60nfNmSb4prHejqzOXQunVrdYsNWkxtJWpIkSKFms+SiBIH1pPkLKcu96IrD7rj4GoousToH0B+EImIyNexDiQiInKyRRLzTaFLDLrNoMuLJ45hISIiig+sA4mIiJwMJDFof8uWLVKuXDmeQyIiSlRYBxIRETnZtTVPnjweMQkmERFRQmMdSERE5GQgOXbsWPnyyy9VSnAiIqLEhHUgERGRk4EkUpZv2rRJpRVHKvCMGTOa3cgD3L4tsnOnSHi4yLhxIps2iRw/LnL/vsi2bZhEzFAO95hf7L8U9nH29Clm4hZ59kzizblzIkuXxlw+fLjIxYsxFodeCpWtEw9LVMR/f7OJiPAI2TL+kITdDrO9v4gIkS1bRJ48sVnk3vn7sm3SYdGiXtxSf2DBCbm2/4bZsudhz9VxPH3wVD3HfdDPB+XZoxecx9OnDbfLl0UOHRJ7nN98WY4sOSVeB59VfHbxGSZyI9aBRERETo6RxNVY8nANGogcPIicziKRkdHLS5USOXpUZP58kY4dRTDR9TvviDRtKrJyZdz3i8m4f/5Z5OuvRYYMEZdDoFqsmIi1eQG/+spws+h23a7CaVlzp5LMObxVOk2uZbZubOut8tnKevL2mK3y61nzdUY//WTYbrduItOmWS3SvNxF2fKgrCw+t0Najaxu8/APLz4lFToWk1x+1+WKydvyfeNt8v2WevLx9CD5+WBd+fqVHTJ6Xz35YsEmGb6znvWNPXokUqQIJoLChEKG4B1BZeHCNvcf+SxSStbNJE8kpVzZc11yVcohXmPRIsNntn59TILn7qOhRIx1IBERkZOBZOfOnW2uu3XrFs+rJ0AQCaZBJCCIhN9+M/wo1+cpW7XKNftFEAlDh8ZPIBkWZj2IjAWCSJjzRwrpNNl83ajVxQ3rztWSX21tAC2dMH26zUASQSQs+SNKWo20fSx7V94UkSJyNco8gEMQCeMO1RWcQQSRMGJXPflv7zHpLXMInPUWYLQ6xxJIooUTQSRc3HfbuwJJfGbh33/dfSSUyLEOJCIicrJrqyUk3lm1apW0bNlScufOzfNKXkMTO6au0bsBExFZ+x5hHUhERIlQnALJc+fOyYABAyRv3rzy5ptvSsqUKWXhwoWuOzoiIiIPxTqQiIgSM4e7toaHh8vixYtl+vTpsnPnTmnQoIFcv35dDh48KKUw/o6IiMhHsQ4kIiJyokXygw8+kJw5c8qECROkTZs2cvXqVVmxYoUkSZJE/Pxc0kuWiIjII7EOJCIicrJFcurUqfLFF1+oOSQx7QcREVFiwTqQiIgomkPNiHPmzJHdu3dLjhw51Dxaf//9t0Rgjj0iIiIfxzqQiIjIyUCyY8eOsm7dOjl69KgUK1ZMevXqpYLKqKgoOY5pB4iIiHwU60AiIqJoTg1szJ8/v3z77bdy4cIFmTt3rrRq1UreeustNfXHxx9/7MwmiYiIvALrQCIiIieytppCkp3GjRur2927d1W3n1mzZvG8EhGRz2MdSEREiZlDLZLVq1eXESNGSHBwcIx1GTNmlD59+sihQ4dceXxEREQegXUgERGRk4Fkz549VbKdKlWqSJEiReSzzz6TLVu2iKZpjmyGiIjI67AOJCIicjKQ7Ny5syxZskRu374tY8eOlQcPHqjsrVmzZpUuXbrIn3/+KWFhYY5skoiIyCuwDvRuWpQmO6cflds3orPNH1hwQq7tv2F8vnvWMVn8yQ55dOOR7Jh6RFYM3C2zu22VP/rtkHXD9xnLbZ14WH7vu12ehz2Xv7/ZbbZu/booWf3dHnn64KnNYzmx6pyc23RJPT70+0mzY7DH3jnH5ebRW+IK2+eelTVD9sqfX+w0LpsxP5ncvxgq++YFy43DIXJx2xV1bkIvhcq2SYdjbGP0guxWt43X6n75K4/x8c0zD+XBlQfyw6ub1H7n9twqYbfDJPjvs/Jbr23qfCz8eLvav6nrB2/KwUUnjc+jIqMbMn7632bj/vBe4/3554e9svmXQxIRbj7DwLNHz2TU65tk1rtb1Htoav/8YLUfUydXn5PT6y5Y/RvvnL6rPivY54s8vPZQnb+oiChxRuSzSPXZe3L3idrvprEH1TJXwd+pfy6J7KK5wM6dO7Wvv/5aK1WqlJYiRQrttdde07Zu3ar5stDQUHxjqHuPhLc2tttrrxnK1a0bvczV+40Pd++++G+zcUivZtwbY102v5svPtw0aV74N+mrO+SL/XM/o8tmq5uyPHy7TuPlyzH/9r/+inX/YXfCjEW3TT6seZVmzeL3s0Vew9O+fxNjHeiN79M/P+xRXx8VZK/6HjkspdTznH7X1Pod044Yv2KSS/R3pent4KIT2qE/Thqfl0h22mZV1K/iRqvHcefMXbU+QJ5qBxaeUI+zJgmx++/YPuWwes1LAeecPhfngi69sCrVb3n9L2up5KF6nE7u2/06R2/Nsu6yujx45VnjceO9wrLDi0+q582z77T6E2Dxp9vNlg1rZP5etM2zzbhuaMPodft/C1bL8vhfMS57cPWBseyjm49inMsqqQyfmxUDd73wvOvHO73zZqfet9HNN6rXv11wi1YuheFYJ3cM0lzh3gXDe5tUnmlP7j1xyTbJ979/ncraaqlq1aoyZMgQOXLkiLrVr19frl+/7opNExEReTTWgd5h9eLH6n6/VFT3+/67vxaVQ91vXXbbWDZcUljdxp6VIbJvVXRr1fGnhW3ub/S+elaXh5y8p+6fS6Bs/9PQEhmiZbH779iy7I66P/28gCSES5G55bGkVo9DJV287efvkCpWlx9aE91aq79X+1YbWh7/ulHV6mt+X2TeOvjj2rLm6y/XMD4evra82fsLlyNzGZfdv/zQ+Dj0SvRj3e7HpdT9ij/C5UX04522OIM4Y9SKoup+zrlacvBJMfV49YZk4gq3z9xX9xESII9uGv6vEL2IU4Hknj17ZNeuXTGWY9m9e/ekb9++0rp1a2c2TURE5NFcWQdOnDhRChQoIMmTJ5eKFSuqvAOxCQoKUuVQvmDBgjJ58uQYZTAEpUSJEpIsWTJ1j2EnpgYPHqwyzpresmc375qIjhEolzNnTkmRIoXUq1dPjh07ZtffRORpomJpN9EkiXgLZiQhnwgke/XqJZcvX46x/OrVq2odERGRr3JVHbho0SKV7bx///5y4MABqV27tjRp0kQuXbI+Run8+fPStGlTVQ7lv/76azV3MwJH3Y4dO1Tugk6dOqks6rhv27ZtjMC3ZMmSqueQfkNvIlM//vijjB49WsaPH68CZwSaDRo0kIcPY7bIEBFR4uRUIHn8+HGpUKFCjOXly5dX64iIiHyVq+pABGpdu3aVbt26SfHixVUSuzx58sikSZOslkfrY968eVU5lMfr3n33Xfnpp5+MZbAOAd9XX30lxYoVU/cYboLlppImTaqCQ/2WJUsWs9ZIlEeA27JlSylVqpT8+uuvKpneb7/9ZvffR0REvs2pQBLdZW7eNM9oBbiqicqJiIjIV7miDnz27Jns27dPGjZsaLYcz7dv3271NWhttCzfqFEj2bt3rzx//jzWMpbbPH36tOq2im617du3l3Pnzpm1fN64ccNsO/ib69ata/PY4OnTpyqbu+mNiIh8l1OBpH61MzQ01Ljs/v37qpsN1hEREfkqV9SBmEYrMjJSsmXLZrYczxHEWYPl1spHRESo7cVWxnSbSA40Z84cWbNmjUybNk2tq1Gjhty5Y0jiopd15Nhg2LBhki5dOuMNratEROS7nGo+HDVqlNSpU0fy5cunuvLAwYMHVSUzd+5cVx8jERGRx3BlHYhEN6bQrdRy2YvKWy5/0TYxDlNXunRpqV69uhQqVEh1X+3Xr5/Tx4bg2vT1aJFkMElE5LucCiRz5colhw8flvnz56vB/Mjo9s4770iHDh0kICDA9UdJRETkIVxRB2bOnFn8/f1jtPCFhITEaAnUYSyjtfLoTpspU6ZYy9jaJqRKlUoFlOjuqm8DsJ0cOXLYvR10f8WNiIgSB6cHNKLi6dGjh2uPhoiIyAvEtQ4MDAxU03isW7dOWrRoYVyO582bN7f6GrQcrlixwmzZ2rVrpVKlSsYAFmWwDUxBYloGXVdjG9sYHBysssECxk0imMR29BZXjOnE1CMjRoxw+m8mIiLf4tQYSUD3nVq1aqnB+hcvXlTLxowZI3/99Zcrj4+IiMjjuKIORDfQ6dOny8yZM1Ugh+APU3/07NnT2FX07bffNpbHcuwLr0N5vG7GjBny6aefGsv07t1bBY4I+E6cOKHu169fr6YZ0aE8gkIk1cG0IJjzEt1QO3furNaj+yrKDx06VM1BefToUenSpYukTJlSOnbs6JLzR0REiTSQRGpyVGQYZ4HJl5EwADJkyBAjxTgREZEvcVUdiPkeUf67776TcuXKyebNm2XVqlVq7KWeBdZ0Tkm0FGL9pk2bVPnvv/9exo0bJ61atTKWQcvjwoULZdasWVKmTBmZPXu2mq8SCXZ0V65cUd1wixYtqqb3QOvozp07jfuFzz//XAWTH3zwgWrxxByZCFDTpEkT5/NHRESJuGvrL7/8ojK9vfHGGzJ8+HDjclQ2pldGiYiIfI0r60AEarhZgyDQEqbg2L9/f6zbRAsjbrYg0HwRtEoOHjxY3YiIiFzWIonuMPq4CVMYZP/48WNnNkkOigiPkM2/HJKw22ExVx458uINXL8usm+fiMVcaLdP3pFlX+2SrRMPixZlyAYIT+4+kfU/7pehDTfJtf2207/HcP68yIkT6uHFbVdky/hDsmPqEXl045HaB7Y7vk2QnN1g6Bqmu38xVGa+s0XO/Gu+3C6YKHz3bvXw+PIzxsV77haWqW9tVucOTq+7IDejslrfxrNnIkFBuHQv8vBh9PJly0SuXhXZtk02jzso9TPul33zgo2r913LKeNaBUnkM0MLhantU45Iv9lljM+Dfj4ov7QOkt2zjpmVO/T7yZjHg2kGtm0TiYoSQevH8uWYzTxmuRYtRPtplGzts1iGNdokY97YpM774cWnYhQ9tOmezOiyRR6HPFafJZyXPb8el5tHb4kzTq05r86pNXfP3pOd04+afabiBOcCE6Pj3oEJ4IlcgXUgERGRky2S6F6DVOem3WBg9erVUqJECZ7XBDCqxVb58p968s4vW2TmKUOCBAXdoMpEBys24Yp2pUoxFjcsHyIHnhi6QP1+Zoe0GV1dPe5dc49MO1FHPe6/Dmng7ThIBGPFiqn7yGs3pWSt9PJYcqtVyd97IuFSRqQXntUVWWy+zVdLXJV9YbVFZouEhz6VZGkdyAR44AAmSpNHF25LyeaFjYtDJZ28N7+OnDqxSb5dVVmKNMxvexvffy/yww8xl/+XFOOQlJG6ckg9rtQpevWp5wWk99ICcqzsZpkSbDhfEPz3WanZs7TZpur1KWd4sMR8F+XaFY2537ZtkTEDA7MMQeWHH1o/7qgo2fHZEqkt0ZOG9/tvyNbp9RclV/nowPmDhYbj6/Yr/i0rzX7YLX+HVJGXAs7LqWdZxBEPrz2Uoo0LqMePbj6WVFlTma1/rdwV2fmotKy4tFuafVdF4qxWLfPnISEiWRw7ZiJnsQ4kIiJyskXys88+k169eqlxF5hXavfu3TJkyBA1GTPWOWLixImqUk6ePLnKYLdly5ZYyyNBAMqhfMGCBWXy5MkxyixZskQFtGghxT2SBZhCVx102zG96enOvcWPawzB4qzTJkEknIlugXPGgSfFjY//+CN6uR5EOiQszBBMogX1whV5LKmNq8IlRawv3RcWfUECgYkzQk+Zt7bqRu2rJ/cvPYj9xdaCSNPjk4qxrp9qcb4OrbV+LHZDEAkIJMePj7XoFrH4TPzn+IbYW5IRRMLp54aA0BH3L0e32lo7twgiYfkf4RIvrl2Ln+0SxXMdSERElKhaJDFfVkREhBqMHxYWprK4YV6tn3/+Wdq3b2/3dlAJYzA/gsmaNWvKlClTVPKC48ePS968ea12J2ratKl0795d5s2bJ9u2bVNjS7JkyWJMNrBjxw6VwABJCJBSHUFk27ZtZevWrWbJBkqWLKky2ekwn5c3iXI+4S4REcWBq+pAIiKiRDmPJII53G7fvi1RUVGSNauNsWaxGD16tHTt2lW6deumniN73Zo1a1RGvGHDhsUoj9ZHBJh6VrzixYvL3r175aeffjIGkljXoEEDlTYdcI9WTCxfsGBB9B+eNKnXtUISEZFncEUdSERE5M2catZ68uSJugoLmTNnVs8RqCE1uL0wufG+ffukYcOGZsvxfPv26PFdptDaaFm+UaNGKph8/vx5rGUst3n69Gk1/xe61eIK8rlz52I9XkzYjHm2TG9ERJT4uKIOJCIiSpSBZPPmzWXOnDnq8f3796VKlSoyatQotRytifbAVVzMvZUtWzaz5Xh+44b1sVxYbq08uhhhe7GVMd0murji+NH6iRTuWIe5t+7cuWPzeNFCmi5dOuMtT548dv2dRETkW1xRBxIRESXKQBJzWNWubUjosXjxYtVF9OLFi6pixeTIjkCiG1NIXGC57EXlLZe/aJsYh4musKVLl5ZXX31VVq5cqZb/+qtKX2kVusiGhoYab5cvX7b7byQiIt/hyjqQiIgoUY2RRJeeNGnSqMfoytOyZUvx8/OTatWqqcrUHugOhAQ3lq2PISEhMVoUdaisrZXHeMdMmTLFWsbWNiFVqlQqqER3V1uQARY3IiJK3FxRBxIRESXKFsnChQvLsmXLVKscuofqYxIRsKVNm9aubQQGBqppPNatW2e2HM/RzdSa6tWrxyiPSrxSpUoSEBAQaxlb29THPwYHB0uOHDnsOnYiIkq8XFEHEhERJcpA8ptvvpFPP/1U8ufPr8YbInjTA7by5cvbvZ1+/frJ9OnTZebMmSqQ69u3r1y6dEl69uxp7E769ttvG8tjOa724nUoj9fNmDFDHYuud+/e6jhGjBghJ06cUPeY5gPTjOhQHplcMZ3Irl27pHXr1ip5TufOnZ05HURElIi4qg4kIiJKdF1bEXjVqlVLrl+/LmXLljUur1+/vpq70V6Y7xEJbr777ju1rVKlSsmqVaskX758aj2WIbDUIcMq1iPgnDBhgsq6ivEo+tQfgJbHhQsXyoABA2TgwIFSqFAhNV+l6RySV65ckQ4dOqgEPZiDEt2Rdu7cadwvERFRfNeBREREiSaQROCGrHT/+9//VIVpOQ8jMtc56oMPPlA3a2bPnh1jWd26dVWigxdV8rjZgkCTiIjI3XUgERFRouja+ttvv0nKlCnl448/Vsly2rRpI3PnzpW7d+/G3xESERF5ANaBRERETgaS9erVU3NlIbvpjh07pEKFCqqLKZLUYN2YMWPk7NmzjmySiIjIK7AOJCIiimOyHShZsqRKhoOxhUiA07FjR9mwYYOaRgNjHfW5GYmIiHwN60AiIkrsnEq2YwnjRHr06KFujx8/VpnrOOciERElBqwDiYgoMXIqkESyG8zbiNZH+Ouvv2TWrFlSokQJGTx4MLPWERGRz2IdSERE5GTX1vfee09OnTqlHp87d07at2+vkvD88ccf8vnnn/O8EhGRz2IdSERE5GQgiSCyXLly6jGCxzp16qhsdpiuY8mSJTyvRETks1gHEhERORlIapomUVFR6vH69euladOm6nGePHnk9u3bPK9EROSzWAcSERE5OUayUqVK8sMPP8irr74qQUFBMmnSJLX8/Pnzki1bNp5XIiLyWa6sAydOnCgjR46U69evq0ywY8eOldq1a9ssj/3169dPjh07Jjlz5lTDSXr27GlWBj2DBg4cqKbjKlSokAwZMsQsd8GwYcNk6dKlcuLECUmRIoXUqFFDRowYIUWLFjWW6dKli/z6669m261atarK1O4uBxackGxF00tgqgA5u/W6VHmnpCTxSyI3j96Ss9tuyPPwSAlM4S+REZpkzp9aCtbJLf1f3i6aJlKrQQpZdqSQ2fbCJbnx8T8/7JWJawq+8Bgm/JFFbj9La/cxz3p3iwRtTqKOoXXHQEmeyl+2r3koIoZ9jV6S31i2f81Nkr+Qn7T5vqyM73pA2n2RX/6ZclFCbmpS9eWUsn7FE/Hz02TM/nrG1/QqHSQtOqWRpIF+snDqA2nxZkqp2bWYnPr3suxfe1saf1hYts07L1fOPZNbt0ROXkoukVFJJHuGp7j8L97go19ekqdPtsqt6xGYhEctW/9vEjlTa5Pxuamd04/K75drmC0LlXTSp3yQpE6lSemKgSISvT5K/CTo54OSs0R6Cdrqb1y+vP8uyV44tfgHoM0lp1p2ZPUV+fWrE/L2kKJyfvctuX8jXESqqHVPn/vJ39/sFj//JOozmCSJSNUOBeW9+mekYslwadU3r/F9v/Ikk+z59bjkrZhFNs88I3/8IVI4z1Pp+kMByV8rtwT9cljCH0XI/ZBncuzgc/ng56Jy5J+rci2qUoy/968bVeXa/hty6O/LcvpQmDTqlkcuHrwnT8MipenAiuIfaPibtChNfu+7Q7IVSKk+L+VaFpQDi8/K5r/uSet+eSXkLD6X+YzbPbjopNy59FhOH3gkXadXl/D74XJwwjapkfGE+Pf+UOTkSZFUqUTy5xd5+FDk4EGRGjVEjh4V2btXpGNHkR07RNDwhOUpU9r3hmM7+B4NDRUJCBApZP7/ljyM5oSDBw9qpUqV0tKmTasNHjzYuPzDDz/UOnTooCUGoaGhGk4f7t0hfZJ7Gt69GO/gv/8aFjpz08yftsm93bhZK0WtMy10757xcfj2ffbs3upmbp+6E73i7l27/54ra4/ZXH1lz7XY/6YXbHuGvOPQ37Pgo21xeVuinzRsqGnFisX6guHyudVVf329Uwu7E2b/Ph1waedVs3Nr62PRvViQ5rRmzWwf8MGDzm+XvI67v39dVQcuXLhQCwgI0KZNm6YdP35c6927t5YqVSrt4sWLVsufO3dOS5kypSqH8ngdXr948WJjme3bt2v+/v7a0KFDteDgYHWfNGlSbefOncYyjRo10mbNmqUdPXpU/S2vvfaaljdvXu3Ro0fGMp07d9YaN26sXb9+3Xi7c8fkuziB36fDi0+q/+o5/a5p5VIEq8drh+1V64oEnLP6tVA11RHb33EiWgp57PT3siffKqa0Xffx5vnnYHjjjS7b1sT20XXuPz/sMVuXXGz/Htg68ZDZ8/eKB2ktc+5QjyfJe5pWr55hRcqUmvb8uaa1bGl4PmqU9Q2++66d/9EPR28X90mTalp4eJy/PxKj0ASqJ50KJG158uSJ9hwfqETA3T9kGEi++BuUgaT5KWEgSb7C3d+/rqoDq1SpovXs2dNsWbFixbQvv/zSavnPP/9crTf13nvvadWqVTM+b9u2rQoATSFwbN++vc3jCAkJUeczKCjILJBs3ry55inv06yuW2J8zX9ScaNa58wPbPzj7oCBN54Da5+B1PLAZZ+N0slPGv8PfVBqk0MBqK11ZeWA+YLHj6MfZ8kSy386e/6jz4r5utu34/z9kRiFJlA96dQYyYIFC8qdO3diLA8PD5ciRYq4oqGUiIjII7miDnz27Jns27dPGjZsaLYcz7dv3271NTt27IhRvlGjRrJ37155/vx5rGVsbRNC0YVMRDJmzGi2fNOmTZI1a1b1N3Xv3l1CQkJi/ZuePn0qDx48MLsRkWM0ScJTRl7DqUDywoULEhkZabUSuXLliiuOi4iIyCO5og5EYjpsw3JMJZ7fuHHD6muw3Fr5iIgIY6I7W2VsbRNtcxhzWatWLSlVqpRxeZMmTWT+/PmyYcMGGTVqlOzZs0deeeUV9TfagrGX6dKlM96QgI+IiHyXQ8l2li9fbny8Zs0aVVHoUCH++++/UqBAAdceIRERkQeIjzowCTJyWAR2lsteVN5yuSPb/PDDD+Xw4cOydetWs+Xt2rUzPkaAiQRD+fLlk5UrV0rLli2tbuurr75SQakOLZIMJomIfJdDgeQbb7yh7lEhde7c2WxdQECA5M+fX125JCIi8jWurAMzZ84s/v7+MVoK0X3UVubX7NmzWy2fNGlSyZQpU6xlrG3zo48+UsHx5s2bJXfu3LEeb44cOVQgefr0aZtlkiVLpm5ERJQ4OBRI6nNH4oorurmgIiQXQBepuXNx2Re1tciWLSL37ol062ZIffyfQ7+flJtnH0mR2vhBkDr69evWoU+VCMbA4LUOwLXsPVJZskqInPlxv4hUMK7740p1WfDRdtm5BWNv6pq9DinHx2wsL4FTfhGZN8+QntnyB8SMGdGP95tv25oPSm2WnNmjJKn6VEan9G5X9YJ80T5IXo34R5L06G7X33VVcsrb/7tvc/3ioafw08hsWeRHfcQ/4qmIHWOckEr8RQ4vPiXn9t1TKcBHTs8gzlLnWgIkUJ6LrF37wvJhYj3F9oQp/nI+eHeM99KavhWCpHrdACldP5tcOnRP7lx7KilS+0uekmll2dQQuRbiL1kyRErZSgGye3uEpEmtGdOjd296RfJnPS2tOqeW80cfy8ud8xpTii89WVK6zTomq+fckkLFAqTeuwUld2XD+7B9yhFZMfuOlCwXIP5Jk8jls88kaYBI2ZKRUit0pST7+2/bBzxhgkhgoGgZMsqmUznlWFRxqdosizx58FyiIjUp1SSPXD10W1KkC5QijdhrgpzjyjowMDBQKlasKOvWrTObmgPPmzdvbvU11atXlxUrVpgtW7t2rWotRCCrl8E2+vbta1YGU3yYtlAiiPzzzz/VOEh7WlExJvTy5csqoCQiItIrFHJ3NqQxY6KzUwUGRj/u0cNY5MSqs8bFSFlumtUrLim9dkoVp19eRXbaXXi3VIpz9rFNUsfuws5s/xfpFa/bj8uthmz12GOL6w3uX7wfa5k+MtqujW2VGlZXmWY5Dr3sWZk+yXeytjpKn/5jxowZajqPPn36qOk/Lly4oNYje2unTp1iTP/Rt29fVR6vs5z+Y9u2bWr6j+HDh6vpP3BvOf3H+++/r6VLl07btGmT2fQeYWFhav3Dhw+1Tz75RE0lcv78eW3jxo1a9erVtVy5cmkPHjyw++9j1lb3f7/y5n3nIJU8dNm2mLU18QpNoHrSoRZJUxgLghu6zOhXaXUzZ85kmO6IH3+MfvzsWfTjqVNFpkxRD4+sv2mcyPaJpJQAMSkXB2fF+Yled0tVu8uGSFaJq3+lvtSVzRJfxsuH8qFMEE+0XWqKL7tzDlkjbbfyjpW+Mkaix17ZEmSjtfW+lt74+N7FB5I2t/0TihPFVx2IcYho6fvuu+/k+vXraiziqlWrVBdSwLJLly4Zy6PlEOvR2jhhwgTJmTOnjBs3Tlq1amUsg5bHhQsXyoABA2TgwIFSqFAhWbRokVStGv19PWnSJHVfr575ZO6zZs2SLl26qC63R44ckTlz5sj9+/dVK+TLL7+stpMmTRp+IIiISHEqkPz2229VxYfuNKhgYksMQERE5EtcWQd+8MEH6mbN7NmzYyyrW7eu7FdDBWxr3bq1utmiJ+ixJUWKFCqZEBERkcsDycmTJ6sKrlOnTs68nIiIyGuxDiQiInJyHklMpGw6cJ+IiCixYB1IRETkZCDZrVs3+e2333j+iIgo0WEdSERE5GTX1vDwcJk6daqsX79eypQpY0w7rhs9ejTPLRER+STWgURERE4GkocPH5Zy5cqpx0ePHjVbx8Q7RETky1gHEhERORlIbty4keeOiIgSJdaBRERETo6RJCIiIiIiosTLqRZJTEwcWxfWDRs2xOWYiIiIPBbrQCIiIicDSX18pO758+dy8OBBNV6yc+fOPK9EROSzWAcSERE5GUiOGTPG6vLBgwfLo0ePeF6JiMhnsQ4kIiJy8RjJt956S2bOnMnzSkREiQ7rQCIiSkxcGkju2LFDkidP7spNEhEReQXWgURElJg41bW1ZcuWZs81TZPr16/L3r17ZeDAga46NiIiIo/DOpCIiMjJQDJdunRmz/38/KRo0aLy3XffScOGDXleiYjIZ7EOJCIicjKQnDVrFs8dERElSqwDiYiInAwkdfv27ZPg4GA1p2SJEiWkfPnyPKdERJQosA4kIqLEzKlAMiQkRNq3by+bNm2S9OnTqzGSoaGhapLmhQsXSpYsWVx/pERERB6AdSAREZGTWVs/+ugjefDggRw7dkzu3r0r9+7dk6NHj6plH3/8Mc8rERH5LNaBRERETrZI/vPPP7J+/XopXry4cRm6tk6YMIHJdoiIyKexDiQiInKyRTIqKkoCAgJiLMcyrCMiIvJVrAOJiIicDCRfeeUV6d27t1y7ds247OrVq9K3b1+pX78+zysREfks1oFEREROBpLjx4+Xhw8fSv78+aVQoUJSuHBhKVCggFr2yy+/8LwSEZHPYh1IRETkZCCZJ08e2b9/v6xcuVL69OmjEuysWrVKpULPnTu3Q9uaOHGiCkKTJ08uFStWlC1btsRaPigoSJVD+YIFC8rkyZNjlFmyZIkas5ksWTJ1/+eff8Z5v0RERImlDkQ29sGDB0vOnDklRYoUUq9ePZVgj4iIyKlAcsOGDapSQnZWaNCggcpeh0q0cuXKUrJkSYcCskWLFqlKuH///nLgwAGpXbu2NGnSRC5dumS1/Pnz56Vp06aqHMp//fXXat+oNHU7duyQdu3aSadOneTQoUPqvm3btrJr1y6n90tERJSY6sAff/xRRo8erVpf9+zZI9mzZ1d/L3oeERERQRINlx3t9L///U/NFYmxkNaMGzdONm7caPXqpzVVq1aVChUqyKRJk4zLkAn2jTfekGHDhsUo/8UXX8jy5cslODjYuKxnz56qskTlCahAUcmvXr3aWKZx48aSIUMGWbBggVP7tQb7SJcunZo/M23atOKMG4dDZPu8cyIjf7Rd6LPP1d2Gf57KhCN1rRZZIi3FWRvlZRkvHzn9env3vU8qylDpL3HRQNZKT4l59d2aVrI0Xv8eZ7cfF558bHGx5LOdcuPSU+m1qG6c//6Z8q6slGaxlpnUYbNkzR3o8HGS5wh7+lg6jXs1Tt+/zkgsdSB+FqAlEsEm9glPnz6VbNmyyYgRI+S9995LsHry1JrzcvTfm/L3sucy63Rts3W10h6Svu89kVYjqzm8XXyfeNt3JZGj/CRS/vhsj3o8ZHw62f8keraF2HQquFXmnqtldZ2/RMjv0jZ6QZ++ImPHvHij//2ejdXevSIbN5gv+/AjkRQpXvxack89qTkgb9682vHjx22uDw4O1vLkyWPXtp4+far5+/trS5cuNVv+8ccfa3Xq1LH6mtq1a6v1pvD6pEmTas+ePVPPsf/Ro0eblcFzHLuz+4Xw8HAtNDTUeLt8+TICcPXYWau/36PhHeCN54CfAX4G+Blw5DMQGufvX2ckljrw7Nmz6vzu37/frMz//vc/7e23307QenLkaxv5f4Pfj/wM8DPAz4B4Zj3p0DySN2/etDrthy5p0qRy69Ytu7Z1+/ZtiYyMVFc4TeH5jRs3rL4Gy62Vj4iIUNvLkSOHzTL6Np3ZL+Aq7bfffiuulD57cqmZ5rBIZIRIWFjMAsmSiQQmMz7d9rCM8XGhpBflbEQ+SS/3pKTEbdzKNrF+1elFcvldk/xR5+J9P7rqsl38JCre9lVcjktGuRtzRfLkIuHhZotOSDG5I5kloeSRS5JX7Ot6fVjKyENJuFaauFL/Byw+35ayyQ0pLGdeuK0o8ZMdUsOu/ZH3itAeya5HCb/fxFIH6vfWyly8eDFB68lcBQLV/1n8Itpu8R1RLfUR8U+i2fzuyOt/RS5FWh+zWtNvu5yMekluSxbxNMnliYSL8y0wKSRMnkhKlx6TLysccEHOPM8f5+2UTHZajj19KUbrXaSDU7YXCTgvp54XiPPx6MeUPvCJehypJZGdj0rbdWz4P2f6/yqf/xW5EZlZnkpyKSlHJX3y8OjfRWnSijx6JKJFiaRMGf17NomfYZnaWVLDuhfSRCy7z2P75LH1pEOf7ly5csmRI0dUllZrDh8+rCoyRyRJksTsObrUWC57UXnL5fZs09H9fvXVV9KvXz+zLjtIuBAX1bqVkq3dnH11vv/uM6CDj7hHzv9uCSX2ACHuSojnyvvfzRfZDiCjZf/vllD7I09m6DKZ8PtNbHWgJ9STHX6pIR1sJoOP/lFsXW431idxEddufAwiHRP3INLAPIg0cCyINHBNEGn7mOw5tjKx/F8qFcdjIl+qJx1KtoNB/t98842EW7TOwJMnT2TQoEHSrFns45N0mTNnFn9//xhXXkNCQmJcBdVhsL+18rgKnClTpljL6Nt0Zr+A7HfoY2x6IyKixCOx1IHYBrCeJCIilwWSAwYMkLt370qRIkVURre//vpLDfzH4PuiRYuqdcgCZ4/AwECVcnzdunVmy/G8Rg3rVwqrV68eo/zatWulUqVKxu5Gtsro23Rmv0RERImlDsS0IAgmTcs8e/ZMTT3CepKIiIwcHVR54cIFrUmTJpqfn5+WJEkSdcNjLDt//rxD21q4cKEWEBCgzZgxQyUw6NOnj5YqVSq1D/jyyy+1Tp06GcufO3dOS5kypda3b19VHq/D6xcvXmwss23bNpVIYPjw4SrxAe6RiGDnzp1279ceGLzqjmQPRESJnTu/fxNLHYjXpUuXTiXlOXLkiNahQwctR44c2oMHD+z++1hPEhG5R0J9/zocSOru3r2r7d69W9u1a5d67KwJEyZo+fLl0wIDA7UKFSpoQUFBxnWdO3fW6tata1Z+06ZNWvny5VX5/Pnza5MmTYqxzT/++EMrWrSoqiiLFSumLVmyxKH92oMVJBGRe3jC96+v14FRUVHaoEGDtOzZs2vJkiVTGV0RUHrb+0RElBiFJtD3r0PzSFI0zMuSPn16uXz5MsdLEhElID2Jy/3799U8heSZWE8SEfl2PelMOikSkTt37qjzENeMdERE5Pz3MANJz8V6kojIt+tJBpJOypgxo7q/dOmSV/yQ0a9MeEsLKo+X55efB/5/i62lK2/evMbvYfJMrCfjF+tJnl9+HhKOt/1/C02gepKBpJP8/AwJbxFEesMHSudtU5fweHl++Xng/7cXfQ+TZ2I9mTBYT/L88vOQcLzt/5tfPNeTrIWJiIiIiIjIIQwkiYiIiIiIiIFkQkiWLJkMGjRI3XsDHi/PLz8P/P/G7wdivcN60l34O4Tnl58H3/v/xuk/iIiIiIiIyCHs2kpEREREREQOYSBJREREREREDmEgSURERERERA5hIElEREREREQOYSAZi4kTJ0qBAgUkefLkUrFiRdmyZUusJzMoKEiVQ/mCBQvK5MmTJSEMGzZMKleuLGnSpJGsWbPKG2+8ISdPnoz1NZs2bZIkSZLEuJ04cSLej3fw4MEx9ps9e3aPPLeQP39+q+eqV69eHnFuN2/eLK+//rrkzJlT7WfZsmVm6zVNU+cc61OkSCH16tWTY8eOvXC7S5YskRIlSqiMX7j/888/4/14nz9/Ll988YWULl1aUqVKpcq8/fbbcu3atVi3OXv2bKvnPDw8PF6PF7p06RJjv9WqVfPI8wvWzhNuI0eOdMv5tef7y9M+wxSN9WT8YD3pWqwnWU868nlgPWk/BpI2LFq0SPr06SP9+/eXAwcOSO3ataVJkyZy6dIlq+XPnz8vTZs2VeVQ/uuvv5aPP/5Y/ZCJbwiyENTs3LlT1q1bJxEREdKwYUN5/PjxC1+LH2zXr1833l566SVJCCVLljTb75EjR2yWdee5hT179pgdK84xtGnTxiPOLd7nsmXLyvjx462u//HHH2X06NFqPf4WBO0NGjSQhw8f2tzmjh07pF27dtKpUyc5dOiQum/btq3s2rUrXo83LCxM9u/fLwMHDlT3S5culVOnTsn//ve/F243bdq0ZucbN1x4iM/j1TVu3Nhsv6tWrYp1m+46v2B5jmbOnKkqzVatWrnl/Nrz/eVpn2EyYD0Zv1hPug7rSQPWk/Z9HlhP7rL/P5dGVlWpUkXr2bOn2bJixYppX375pdXyn3/+uVpv6r333tOqVauW4Gc4JCREw1sbFBRks8zGjRtVmXv37mkJbdCgQVrZsmXtLu9J5xZ69+6tFSpUSIuKivK4c4v9/vnnn8bnOMbs2bNrw4cPNy4LDw/X0qVLp02ePNnmdtq2bas1btzYbFmjRo209u3bx+vxWrN7925V7uLFizbLzJo1S/1N8c3a8Xbu3Flr3ry5Q9vxpPOLY3/llVdiLZNQ59fa95enf4YTM9aT8Yf1ZPxhPRm/WE/GP0+qJ9kiacWzZ89k37596qq4KTzfvn27zavfluUbNWoke/fuVd31ElJoaKi6z5gx4wvLli9fXnLkyCH169eXjRs3SkI5ffq06lKArsPt27eXc+fO2SzrSecWn4158+bJu+++q1pxPPHcWrbm3rhxw+z8oZtf3bp1bX6WYzvnsb0mPj/PONfp06ePtdyjR48kX758kjt3bmnWrJlqvU4o6M6MbplFihSR7t27S0hISKzlPeX83rx5U1auXCldu3Z9YdmEOr+W31++8Bn2Rawn4x/ryYThC98xrCfjD+vJ2DGQtOL27dsSGRkp2bJlM1uO5/iysQbLrZVHNy1sL6HgYlC/fv2kVq1aUqpUKZvlEOBMnTpVdQ9F98GiRYuqgAf9xuNb1apVZc6cObJmzRqZNm2aOnc1atSQO3fuePS5BfSjv3//vhoX54nn1pL+eXXks6y/ztHXxAeMwfvyyy+lY8eOqkuOLcWKFVPj+JYvXy4LFixQXS5r1qypfojFN3R5nz9/vmzYsEFGjRqlul6+8sor8vTpU48/v7/++qsam9iyZctYyyXU+bX2/eXtn2FfxXoyfrGeTDje/h3DejJ+sZ6MXdIXrE/ULFuc8CMntlYoa+WtLY9PH374oRw+fFi2bt0aazkEN7jpqlevLpcvX5affvpJ6tSpE+8/vHVIqoJ9FypUSP1nxY9ITz23MGPGDHX8aE31xHPrqs+ys69xJbQ2o7U6KipKJfSIDZLbmCa4QZBToUIF+eWXX2TcuHHxepwYh6dD8FOpUiXVcoeWvtgCNHefX8D4yDfffPOFYx0T6vzG9v3ljZ/hxID1ZPxgPZnwvPE7hvVk/GM9GTu2SFqROXNm8ff3j3FVCd3VLK8+6ZD8wVr5pEmTSqZMmSQhfPTRR6rFAN0o0f3MUfihmBAtOJaQnRMBpa19e8K5hYsXL8r69eulW7duXnNu9Wy4jnyW9dc5+hpXV45IjIIuR0jAEltrpDV+fn4qE6g7zjlapBFIxrZvd59fQBZqJIRy5vMcH+fX1veXt36GfR3ryYTFejL+eOt3DOvJ+Md68sUYSFoRGBiopprQs3Pq8BxdMK1Bq5Nl+bVr16rWiYCAAIlPuAKGK/noRonudRh36AyMecKP4ISGLoDBwcE29+3Oc2tq1qxZahzca6+95jXnFp8FVHam5w9jm5Ap09ZnObZzHttrXF05IkhB4O7MxQL8nzh48KBbzjm6aKMFOrZ9u/P8mrau43sOmevceX5f9P3ljZ/hxID1ZMJiPRl/vPE7hvVkwmA9aQen0gUlAgsXLtQCAgK0GTNmaMePH9f69OmjpUqVSrtw4YJaj+ytnTp1MpY/d+6cljJlSq1v376qPF6H1y9evDjej/X9999XmZk2bdqkXb9+3XgLCwszlrE83jFjxqhsjqdOndKOHj2q1uPjsGTJkng/3k8++UQdK87Zzp07tWbNmmlp0qTxyHOri4yM1PLmzat98cUXMda5+9w+fPhQO3DggLphP6NHj1aP9SynyOKFz8fSpUu1I0eOaB06dNBy5MihPXjwwLgNHL9pRuJt27Zp/v7+6rXBwcHqPmnSpOr9is/jff78ufa///1Py507t3bw4EGzz/PTp09tHu/gwYO1f/75Rzt79qza1jvvvKOOd9euXfF6vFiHz/P27du18+fPq4y91atX13LlyuWR51cXGhqq/k9NmjTJ6jYS8vza8/3laZ9hMmA9GX9YT7oW60nWk458HoD1pH0YSMZiwoQJWr58+bTAwECtQoUKZtNpIOV/3bp1zcrjh1D58uVV+fz589v8keZq+E9g7YaU/baOd8SIEWoKi+TJk2sZMmTQatWqpa1cuTJBjrddu3bqRyCCwZw5c2otW7bUjh07ZvNY3XludWvWrFHn9OTJkzHWufvc6tONWN5wXHpaaKSSR2roZMmSaXXq1FE/xk3h+PXyuj/++EMrWrSoep8w/YqrAuHYjhfBmK3PM15n63hxoQeBPj4fWbJk0Ro2bKiCu/g+XgQ72Bf2ifOEY8DyS5cueeT51U2ZMkVLkSKFdv/+favbSMjza8/3l6d9hika68n4wXrStVhPsp505PMArCftkwT/2NNySURERERERAQcI0lEREREREQOYSBJREREREREDmEgSURERERERA5hIElEREREREQOYSBJREREREREDmEgSURERERERA5hIElEREREREQOYSBJREREREREDmEgSeRCgwcPlnLlynnMOU2SJIksW7bM4dedPHlSsmfPLg8fPoyX4/JmISEhkiVLFrl69aq7D4WIyOuwnvR9rCcTDwaS5HUmT54sadKkkYiICOOyR48eSUBAgNSuXdus7JYtW1QwderUKfFlrq6Y+/fvL7169VLn2VLRokUlMDDQLYHUhQsX1Pt58OBBcZesWbNKp06dZNCgQW47BiKi2LCejIn1ZMJhPZl4MJAkr/Pyyy+rwHHv3r1mASNa0Pbs2SNhYWHG5Zs2bZKcOXNKkSJF3HS03ufKlSuyfPlyeeedd2Ks27p1q4SHh0ubNm1k9uzZ4qmePXsWr9vHuZk/f77cu3cvXvdDROQM1pPxi/Xki7GeTBwYSJLXQYsYgkMEiTo8bt68uRQqVEi2b99uthwVKsybN08qVaqkWtkQdHbs2FF1v4CoqCjJnTu3uoprav/+/aoF7Ny5c+p5aGio9OjRQ11tS5s2rbzyyity6NChWI931qxZUrx4cUmePLkUK1ZMJk6cGKOFbenSpeo4U6ZMKWXLlpUdO3aYbWPatGmSJ08etb5FixYyevRoSZ8+vVqHgO7bb79Vx4Ft4WYa5N2+fVu9Bq996aWXVJAYm99//10dA86HpRkzZqjzhha5mTNniqZpZuvz588vQ4cOlXfffVed57x588rUqVPNyuD9QespzgfeD3S9NW1lRHD25ptvqu6jKVKkUMeMcwgFChRQ9+XLl1evqVevnnrepUsXeeONN2TYsGFmFw6OHDmi3iNsJ1OmTOq9w0UInf46HHO2bNnUOcW5RGv3Z599JhkzZlTnAX+rqdKlS6vP0J9//hnruSQicgfWk6wnWU9SgtCIvFDHjh21hg0bGp9XrlxZ++OPP7T3339f+/rrr9Wyp0+failSpNCmT5+uns+YMUNbtWqVdvbsWW3Hjh1atWrVtCZNmhi38cknn2i1atUy2w+WVa9eXT2OiorSatasqb3++uvanj17tFOnTqn1mTJl0u7cuaPKDBo0SCtbtqzx9VOnTtVy5MihLVmyRDt37py6z5gxozZ79my1/vz584jEtGLFiml///23dvLkSa1169Zavnz5tOfPn6syW7du1fz8/LSRI0eq9RMmTFDbSJcunVofFhamjqNkyZLa9evX1Q3LANvOnTu39ttvv2mnT5/WPv74Yy116tTG47WmefPmWs+ePWMsf/DggZYqVSrt6NGjWkREhJYtWzZtw4YNZmVw3Dg2HCP2N2zYMHXswcHBxm1g/VtvvaUdO3ZMvR9FihRRx3ngwAFVplevXlq5cuXUOcb5WbdunbZ8+XK1bvfu3ars+vXr1d+p/x2dO3dWf1enTp3U8R05ckR7/PixljNnTq1ly5bq+b///qsVKFBAldXhcZo0adQ+T5w4oT4j2H6jRo20IUOGqPf4+++/1wICArRLly6Z/a1t27bVunTpYvM8EhG5E+tJ1pOsJym+MZAkr4QADUENgi0EJ0mTJtVu3rypLVy4UKtRo4YqExQUpIICBI7W6EHJw4cP1fP9+/drSZIk0S5cuKCeR0ZGarly5VJBESAQSZs2rRYeHm62nUKFCmlTpkyxGkjmyZNHBXGmEJjowakeSOrBLiDAwjI9+GrXrp322muvmW3jzTffNAaS1varw3YGDBhgfP7o0SP1N65evdrmucV2vvvuO6vnHAGernfv3uo4LANJBIk6BN9Zs2bVJk2apJ7jHoH3kydPjGWmTZtmFkgiUH/nnXesHpt+vvSypgEhAltcPDA93gwZMqi/Wbdy5UoV2N64ccP4Ohwz3mtd0aJFtdq1axufI2jGZ23BggVm++zbt69Wr149q8dJRORurCdZT5piPUnxgV1bySuhG+jjx4/VmEiMj0RXRnQ3rVu3rlqGdejWiq6VBQsWVK85cOCA6v6aL18+1e1S7xZ56dIlYzcQdD1dsGCBeh4UFKS6vrZt21Y937dvn+oWiS6SqVOnNt7Onz8vZ8+ejXGMt27dksuXL0vXrl3Nyv/www8xypcpU8b4OEeOHOpe73aLDKpVqlQxK2/5PDam206VKpX62/VtW/PkyRPV7dRat9a33nrL+ByP0SX3/v37NveH7qfoAmr6t2C96fYt/5b3339fFi5cqLq/fv7552ZdlWOD7qZIAqQLDg5WXXTxN+tq1qypujHjOHQlS5YUP7/or0J0ccW2dP7+/uo9tzxn6C5rOh6XiMiTsJ5kPWmJ9SS5WlKXb5EoARQuXFiNXdu4caMaU4cAEhC0YBzdtm3b1DqMjwMElg0bNlQ3jJXE+DsEkI0aNTJLzIKxeb/99pt8+eWX6h7rM2fOrNYhAEGQZzo2U6ePVzSF8vr4xqpVq5qtQ3BiChlnTYMv09ejYVFfprMcmxgb023r29e3bQ3+XsskMsePH5ddu3apIP2LL74wLo+MjFSBN4I/e/Znz9/SpEkTuXjxoqxcuVLWr18v9evXVxlkf/rpp1j/TtOA0da+TI8ptuO155zdvXtXfY6IiDwR60nWk5ZYT5KrsUWSvPpqK4I63PTWRUBQuWbNGtm5c6cx0c6JEydU0pnhw4erKULQ8mitVQ6JZJCgBa2PixcvVoGlrkKFCnLjxg1JmjSpqqBNb3qwaQotW7ly5VKJeizL60lj7IFj3b17t9ky04y1gJY4BHWugJZZBI6WrZF16tRRCX2QFEe/ocUQ6xz5Ww4fPixPnz61+bcAAjQkwkHQP3bsWGPCHr3F0Z6/tUSJEuoYcRFBhwsMaH10RRbfo0ePqnNFROSpWE9GYz0ZE+tJiisGkuTVFSSmo0CwoLdIAh6jFRDTVOiBJLq4ohL55ZdfVGCHzKXff/99jG0iwKtRo4bqjorMnegKq3v11VelevXqKssnAlVkXEW3ywEDBlgNhvR5q5BJ9Oeff1ZzWSJIRQZSZF2110cffSSrVq1Srzl9+rRMmTJFVq9ebdaqhmyp6GKLc4GA2TRQcxRaYZE1Vg/Wnj9/LnPnzpUOHTpIqVKlzG7dunVTQfeLMteaBupo2UP2VHQ9xXnUWxr1v+ebb76Rv/76S86cOSPHjh2Tv//+W2W9BXRfRpfSf/75R27evKmy6NqCiwDoQtu5c2cV9KGFGucSGWcR5McFurTi70YLNxGRp2I9yXqS9STFJwaS5NUVJMbzoYXPNDBAIPnw4UM1FQimzNBbuDAlxh9//KGuwKFl0lZXSQQgCIxatmypghYdAh0EdGiZw/QWaNVq3769CihtBSYItKZPn672jbEJODY8dqRFEuP6MC0JAkmM+UMQ1bdvX7Nxhq1atZLGjRurc4K/VR/n6YymTZuqrp3oVgoIuu/cuaOmELGEqTnwd9nbKokpU1asWKECXoyB7N+/vwocQf97EPB/9dVXaiwlzjW6AWPMJKA1eNy4cSqYxjQfpoG+JUx3gkAVXVArV64srVu3Vt1kx48fL3GFQBcXJ9C6TUTkqVhPsp5kPUnxKQky7sTrHojI5bp376666yLRUHzAXJcIlhCIxbf58+eriYtx1dQ0cPdkSBDUp08f1cJKRESeh/Wke7GeTByYbIfIC6D1tEGDBmqgPLq1/vrrryrYiy/oeoqEO2jZRZZXV5ozZ47KpIvxo2j5RfIeZMb1liASY2vRuomuvkRE5BlYT3oO1pOJB1skibwAAi0kFUJghyAMY/169uwp3ujHH39UQTASFyELLsacDhkyRHVFJSIicgbrSaKEx0CSiIiIiIiIHMJkO0REREREROQQBpJERERERETkEAaSRERERERE5BAGkkREREREROQQBpJERERERETkEAaSRERERERE5BAGkkREREREROQQBpJERERERETkEAaSRERERERE5BAGkkREREREROQQBpJERERERETkEAaSRERERERE5BAGkkQUJwMGDJBmzZpJrly5JEmSJNKlSxeeUSIiIiuuXLkiffr0kbp160r69OlVvTl79myeK/JKDCSJKE7GjBkjd+7ckf/9738SGBjIs0lERGTDmTNnZP78+aq+bNq0Kc8TebWk7j4AIvJuDx8+FD8/wzWpuXPnuvtwiIiI3KJevXqSP3/+WFsY69SpI7du3VKP9+7dKwsWLEjAIyRyLbZIEnmgwYMHq+4uhw8fljZt2ki6dOkkY8aM0q9fP4mIiJCTJ09K48aNJU2aNKrS+vHHH81e/+DBA/n000+lQIEC6qonup2iK83jx4/Nyt2/f1+6du2qtp06dWp57bXX5Ny5c2rfOAZ76EEkERFRfPGmejE2rDPJl7BFksiDtW3bVt566y157733ZN26dapifP78uaxfv14++OADVSn+9ttv8sUXX0jhwoWlZcuWEhYWpsZeYBzG119/LWXKlJFjx47JN998I0eOHFGvRYUYFRUlr7/+uroiisqxQoUKsmPHDlURExEReSLWi0QeRCMijzNo0CAN/z1HjRpltrxcuXJq+dKlS43Lnj9/rmXJkkVr2bKlej5s2DDNz89P27Nnj9lrFy9erF67atUq9XzlypXq+aRJk8zK4fVYjmNwVKpUqbTOnTs7/DoiIiJvqhejoqLUfkxvderU0d5+++0Yy23B8WC7s2bN4ptPXol90og8GLKhmipevLhqTWzSpIlxWdKkSVVr5MWLF9Xzv//+W0qVKiXlypVT3X30W6NGjdRrN23apMoFBQUZr+6a6tChQ4zjMN0ObpqGuo+IiChx1osoGxAQYHbbvHmzzJkzJ8byCxcuxMu5IHI3dm0l8mAYo2EK4zpSpkwpyZMnj7Ec4z/g5s2bKiscKi9rbt++re6RaRWVreU+smXLZvYcFSDGlJjauHGjSipARESU2OpFqFixouzZs8dsGYah5MyZUwYNGmS2HMuIfBEDSSIfkzlzZkmRIoXMnDnT5nrIlCmTuiJ79+5ds0rzxo0bMSpAy8qyaNGi8XLsREREnl4vApL6VKpUKcYybMNyOZGvYiBJ5IPdfoYOHaoqM8uWRFNIyIPkPYsWLZL333/fuHzhwoUxruqyUiQiIm/l6nqRiAwYSBL5GKQzX7JkiZqrqm/fviprKzK0Xrp0SdauXSuffPKJVK1aVWVnrVmzpnqO7j/opoOsrRjf4UiKcowT0efEioyMVGNSFi9ebKyUs2TJEo9/LRERkWfViy+i15GYVgSQPR1TjUDr1q35dpLXYCBJ5GNSpUolW7ZskeHDh8vUqVPl/PnzqktP3rx55dVXX1Xza+kV4ooVK1SFibLPnj1TFei8efOkWrVqkj59erv2h7EgeoICQNICPXEBx1ISEVFiqxdfBPNgmpowYYK6AZPZkTdJgtSt7j4IIvIcmJfyzTfflG3btkmNGjXcfThERERuxXqRyDoGkkSJ2IIFC+Tq1atSunRpdSV2586dMnLkSClfvrxZKyMREVFiwHqRyH7s2kqUiCHDHJII/PDDD/L48WPJkSOHdOnSRT0nIiJKbFgvEtmPLZJERERERETkENeknyIiIiIiIqJEg4EkEREREREROYSBJBERERERETmEyXachIlsr127pgZlJ0mSxNnNEBGRgzBr1cOHDyVnzpwumyCcXI/1JBGRb9eTDCSdhCAyT548rn03iIjIbpcvX5bcuXPzjHko1pNERL5dTzKQdBJaIvU3KG3atK58T4iIKBYPHjxQF/L072ESmThxopoD9vr161KyZEkZO3as1K5d2+apwTyx/fr1k2PHjqkr1p9//rn07NnTuH7p0qUydOhQOXPmjDx//lxeeukl+eSTT6RTp052n27Wk0REvl1PMpB0kt6dFUEkA0kiooTHYQUGixYtkj59+qhgsmbNmjJlyhRp0qSJHD9+XPLmzRvjvJ0/f16aNm0q3bt3l3nz5sm2bdvkgw8+kCxZskirVq1UmYwZM0r//v2lWLFiEhgYKH///be88847kjVrVmnUqJFD7w/rSSIi36wnOY9kHCL9dOnSSWhoKANJIqIExO9fc1WrVpUKFSrIpEmTjMuKFy8ub7zxhgwbNizG+fviiy9k+fLlEhwcbFyG1shDhw7Jjh07bJ537OO1116T77//nu8TEZEHS6h6klkKiIiIvNSzZ89k37590rBhQ7PleL59+3arr0GwaFkerYx79+5V3VitJW34999/5eTJk1KnTh2bx/L06VP148X0RkREvouBJLlPVBQG6oiEhPBdICJywu3btyUyMlKyZctmthzPb9y4YfU1WG6tfEREhNqeDleyU6dOrbq2oiXyl19+kQYNGtg8FrR+4gq4fmNCOkpQT5+KrF8v8ugRTzxRAuEYSXKfX38VefddkRIlRI4d4ztBLoeWFPw4xg9t8i4BAQHi7+/v7sPw2nEw+OzHNjbGWnnL5UjScPDgQXn06JFqkURynoIFC0q9evWsbvOrr75SZSyTPRAliAEDRH76SQTjfBcv5km3E+tJ7+Tv7y9JkyZ1e64ApwLJO3fuyDfffCMbN26UkJAQNVeUqbt377rq+MiXbdxouD9+3N1HQj7a5Q8ZLMPCwtx9KOQEVI5IWY4WMV/kqno0c+bM6geFZesjtmnZ6qjLnj271fL4UZIpUybjMsw9VrhwYfW4XLlyakwlWh1tBZLJkiVTNyK30McIL1nCN8BOrCe9W8qUKSVHjhyq14hXBZJvvfWWnD17Vrp27aoqKndHw0REpvCjHJkp8QMbUxvgS5bfU951hfzWrVty5coVNe2EL7ZMuqoexWe7YsWKsm7dOmnRooVxOZ43b97c6muqV68uK1asMFu2du1aqVSpkmoJju19wThIIvJ+rCe9l6Zp6iIA6kn81kE9iQt/XhNIbt26Vd3Kli3r+iMiIoojfMGikkS3OlyxI++DqSguXLigkr/4YiDpynoU3UkxvyMCQQSJU6dOlUuXLhnnhUSX06tXr8qcOXPUcywfP368eh2mAEHynRkzZsiCBQuM20TLI7ZXqFAh9f9p1apV6vWmmWGJyHuxnvRuKVKkUBf+Ll68qN7L5MmTe08giXmlnjx54vqjISJyIXddoaO48/UWZFfWo+3atVNdZb/77jvVnbtUqVIq8MuXL59aj2UILHUFChRQ6/v27SsTJkxQrfbjxo0zziEJjx8/VnNLolUYP1hwvJhzEvsiIt/BetJ7+XnAbxyn5pHcs2ePfPnll2p8Byosy64w8TlfiafgPGYu8PbbInPnGh47/jEksik8PFx198APZnddpaP4ew994fs3MdSjvvA+kRfBeOrHjw2P+ZvihVhPer9wD6gnnWqRTJ8+vTqwV155xWqWOGZIJCIiYj1KlGD0IJKIEoxTbaJvvvmmGuD/22+/qZTgGzZsUDdkn8O9IyZOnGiMpJEwYMuWLbGWDwoKUuVQHmnIJ0+ebLZ+2rRpUrt2bcmQIYO6vfrqq7J79+4475eIyBcgiy26MOIKJS783b9/3y3HMXjwYJUJNLFyZT1KRESuw3oynlskjx49KgcOHJCiRYtKXCxatEj69OmjgrqaNWvKlClTpEmTJnL8+HHJmzdvjPJovm3atKlKDoCxGtu2bVNjOJCUQR/bsWnTJunQoYPUqFFDBYk//vijNGzYUI4dOya5cuVyar9ERL7i119/VRfOtm/frqaOQNcXSniuqkeJyIKPThlECYf1ZDy3SCKT2+XLlyWuRo8erVKfd+vWTYoXLy5jx45VWRZtZYVD6yMCPZRDebzu3XfflZ8wAe1/5s+fr4JLXOlGcgC0UCJ7I674OrtfIiJfgSkn8L2HcXmYT9DXk9p4KlfVo0RE5FqsJ+M5kPzoo4+kd+/eMnv2bNm3b58cPnzY7GYPpKrFa9FaaArPcaXcGqQotyzfqFEj2bt3r0oRb6t5GusyZszo9H4Bc2dh4KrpjYi8CJIvYAyNO24OJH7Aha8RI0aoieAxuTsung0ZMkStO3LkiBqbjiyamDi+R48e8ujRI+Nru3TpIm+88Ya6uIZJilGmV69exu9HTCQ/atQo2bx5swog9Ynl8XjZsmUxxsLjO17/3vzwww/VNtHTI3/+/Gp6CB3GzONYsmbNqrrM4hgPHTpktr3hw4er+RLTpEmjLuQhSUBi5op6lIjIJ+pJB5MjsZ708q6tevpvtAbq8EPEkWQ7t2/fVuXww8IUnt+4ccPqa7DcWvmIiAi1PfzIsYSseOjSirGSzu4X8KPp22+/feHfRUQeKizMfV2eEOylSmVXUcz5h54UY8aMkVq1aqmpG06cOKEuijVu3FiqVaumMn6GhISoXhUI8PSADzDGDt+FuD9z5oz6vkYPDQwJWLp0qfpORLdKPMYYPXtgaojly5fL77//rgJbtKTprWn43n/ttdfUxTpMKYGushguUL9+fTl16pRajtcNGjRITTWBMexz585V28Q498TKFfUoEZFP1JMO1JHAetLLA0mMVXQVy25VeiXqSHlrywHjIzHBMsZNWqbFdXS/+NBi8mYdWiTRHZaIyFUePnwoP//8s5osvnPnzmoZJoRHQIngEvMOYlL4VP9VuCj3+uuvqxZM/eIYkoxhub+/v+rejyAPXfsRSCKoS5kypQog0a3VXpiD8KWXXlLHge9JfX5CQMCKllIEtmhBBbSIooVz8eLFqqUSwwcQMCHwhR9++EHWr1+fqFslXVmPEhElFqwnfSCQNP0R4SwkecAPHctWQPwYsWwt1OGHj7XySZMmVV24TOGHzNChQ9WPlTJlysRpv4AfSPqPJCLyQilTGq56umvfdggODlbd6NGaZ21d2bJljUEkIFkYuvicPHnS+P1VsmRJ9R2nQ+skAr24QJfZBg0aqMQwaBVt1qyZcXgAumWie63ldzCCXowz0Y+9Z8+eZuurV6+ugtDEyhX1KBGRT9STdtaRwHrSBwJJwA8EXGXGG4or1EjegPEeuHpuD1wRx7Qb69atkxYtWhiX43nz5s2tvgY/PFasWGG2bO3atSppgelkziNHjlRXvNesWaPWxXW/ROQD0OPAga4z7oCxj7bE1mvCdLnlxPZYh2AzNnqXSlOm484rVKigWtBWr16tLs61bdtWDRdAiyO2jWAVPT8sYZwlxV89SkTkUqwnYzk1rCddlmwHAVqJEiXU/Ixo7UP2v127dqkr4QjI7IWuotOnT5eZM2eqirRv376qC5V+5RrdSd9++21jeSy/ePGieh3K43UzZsyQTz/91Kw764ABA9Q6JIRAyyNupgkpXrRfIiJ3QPdRBJOmWaZ1+M49ePCgPDaZdBtTIPn5+UmRIkXitF9MoYSxmLrTp0+rMZmmkEQH4/rQxRZTKC1ZskTu3r2rgkx8x6JnCBIEmd7QAwQQIO3cudNse5bPExtX1aNERIkJ60kfaJFEsgYEX8jCZ7n8iy++UF2g7IEfJXfu3JHvvvtO/YhBRYpkDXqXHyxDgKcrUKCAWo99I2lDzpw5VcIGfQ5JwNyQyDDYunVrs30h0QMmwLZnv0RE7oCx3PgO/fzzz1XvCXRdvXXrlpoHFxPY43sMYyfxXYblyPzZqVOnWLvl2wNZVjGuEol80MKIYzBt2UTiH7Q6ImkPAtc//vhDDTVAiyNaJtFbBNliMVYT3V+vXbumvlOxDL1C0MqG48ZjjLPENE34mxJzsh1X1aNERIkJ60kfCCTRiocsfJaQTAHddByBOR9xs8Y0E6Gubt26sn//fpvbu3DhQpz3S0TkLgMHDlSte998840KyBDAobcEkuSgFQtBWeXKldVzXETDvLhxhSlB3nnnHalTp466QIeEPxj7qEudOrUKEtFSifGX2D8CRQSVgMf9+/dXdQACXASZ2JYe4OLiHbpxIkBCgh0c9/vvv6/+nsTKlfUoEVFiwnrScyTRLAfG2AHZSvHjpU2bNmbLUSmim6lpK6KvQtZWpLnH/Gno8kVOQLfluXMNjx3/GBLZhGAFY/rQi8EyYzN5/3voC9+/iaEe9YX3ibyIPlYc01c8fOjuo/F4rCe9X7gH1JNOtUgijTxSup87d05q1KihBqBu3bpVXbH+5JNPXH+UREREPoT1KBERebukzjYpp0mTRnWHQkIcQHcojNv5+OOPXX2MREREPoX1KBERJbpAMiIiQiVK6NChg0oUgIlBAYElERERsR4lIiLf5/D0H0gCgSQJmDRbDyAZRBIREbEeJSKixMOpeSSrVq0qBw4ccP3REBERJQKsR4mIKFGOkcS0GUiqc+XKFalYsaKkSpXKbD0mVyYiIiLWo0RE5JucCiQxJxiYJtZB5lbMJIL7yMhI1x0hESUe6DIfGBidxp3IR7EeJSKiRBlIYs4SIiKXOnRIpGZNkdq1RVav5skln8Z6lIiIEmUgefHiRTV/JBLvWGZ03b59u+TLl89Vx0dEicWff4o8fizyzz/uPhKieMd6lIiIEmWynZdfflnu3r0bY3loaKhaR0TkME3jSYvFhQsX1NCBgwcPesV5yp8/v4wdO9bdh+GxWI8SEbkW60kvCST1sZCW7ty5EyPxDhEREbEeJSKiRNy1tWXLluoeQWSXLl0kWbJkxnVIsHP48GHV5ZWIiIhYjxIRke9yqEUyXbp06oYWyTRp0hif45Y9e3bp0aOHzJs3L/6OlogoDj1nMQTTHTdHeu1GRUXJiBEjpHDhwupiXd68eWXIkCFWyx4/flyaNm0qqVOnlmzZskmnTp3k9u3bxvX//POP1KpVS9KnTy+ZMmWSZs2aydmzZ2N0A1q6dKnqapkyZUopW7as7Nixw2w/GPtep04dSZEiheTJk0dl7H6MP+w/ISEh8vrrr6v1BQoUkPnz5zv25iQirEeJyFO5q550dGQL60kvbZGcNWuWcezLp59+ym6sROQ1wsJEUqd2z74fPRKxt9f/V199JdOmTZMxY8aoIPD69ety4sSJGOWwvG7dutK9e3cZPXq0PHnyRL744gtp27atbNiwQZVBsNevXz8pXbq0evzNN99IixYt1DhLP7/o64j9+/eXn376SV566SX1uEOHDnLmzBmVUO3IkSPSqFEj+f7772XGjBly69Yt+fDDD9VNrxPQQ+Xy5ctqv4GBgSrQRHBJMbEeJSJP5a560pE6ElhPehDNCWFhYdrjx4+Nzy9cuKCNGTNGW7NmjZZYhIaG4vqJuicndeqEi1CGG9E337js8/DkyRPt+PHj6l736FH05hP6hn3b48GDB1qyZMm0adOmxVh3/vx59Z1z4MAB9XzgwIFaw4YNzcpcvnxZlTl58qTV7YeEhKj1R44cMdvm9OnTjWWOHTumlgUHB6vnnTp10nr06GG2nS1btmh+fn7q/GJfKL9z507jerwWy1AvuPI99KXv38RQj/rC+0ReRP/CTZ3a3UfiFTypnrS3jgTWk55VTzo1/Ufz5s3VeMmePXvK/fv3pUqVKuoqNLpU4cr4+++/7/qIl4goDlKmNFz1dNe+7REcHCxPnz6V+vXrv7Dsvn37ZOPGjapbqyV0Xy1SpIi6HzhwoOzcuVN9P6M7EFy6dElKlSplLF+mTBnj4xw5cqh7tCgWK1ZM7Qetk6bdVfGTDdvCXIinTp1SLZeVKlUyrsfr0J2WbGM9SkSexl31pL11JLCe9CxOBZL79+9X3a5g8eLFanzkgQMHZMmSJarrFANJIvI0SDTt6UmlMcbQXgjkMC4R4ykt6cEg1mNMI7rK5syZU70GAeSzZ8/MygcEBBgf6xm59aAT9++9957qrmoJ4zdPnjxp9jqyD+tRIvI0rCdZTyZIIBkWFqaS7cDatWtV6yTG21SrVk1NskxERI7DGEUEk//++69069Yt1rIVKlRQF+8wZh0tgtamY8KV2ylTpkjt2rXVsq1btzp8TNjPsWPHVPIfa4oXLy4RERGyd+9e1TsFEFyitwrZxnqUiMhxrCd9YB5J/KBYtmyZSq6wZs0aadiwobErVNq0aV19jEREiULy5MlVwpzPP/9c5syZo7qmolsqktxY6tWrl9y9e1clxtm9e7ecO3dOXdh799131XRMGTJkUJlap06dqrqmIhEOEu84CseDLK7YH5L0nD59WpYvXy4fffSRWl+0aFFp3LixSvqza9cu1RUWQbAjrauJEetRInLG7ZN3RItyMM2pD2E96QOBJLqvImsrroRXrVpVqlevrpbjR0z58uVdfYxERIkGxjR+8skn6nsWrX3t2rWzmgEVXVW3bdumgkZkVUWX1d69e6vpJdBDBLeFCxeqwA7r+vbtKyNHjnT4eDB+MigoSAWQaNnEdzyOUe8+q2ciRRdaZJFFDxVMBZU1a9Y4nwtfxnqUyMXpRhOBX7tvlSzFMsn7pbZIYsZ60oM4m6Xn+vXr2v79+7XIyEjjsl27dhkz/dlrwoQJWv78+VWmwgoVKmibN2+OtfymTZtUOZQvUKCANmnSJLP1R48e1Vq2bKnly5fPZtbAQYMGqXWmt2zZsjl03MxG5wLM2koJmLWVvIsnZKOLb66qRz2Vr7xP5AXOnImuP6pV03xViWSnXZbsnvWk93viAfWkU2MkAQl2cDOlj4+x16JFi6RPnz4yceJEqVmzphrL06RJEzXJNpI4WEKGQEy+jS5U8+bNU1fjP/jgA8mSJYu0atXKOO6kYMGC0qZNG3UF3paSJUvK+vXrjc/9/f0dOnYiIqK4cEU9SkRxSAHqZZ5H8bcqeRanAklMaG0tQx+Woe8yxn507NhRjZ2JDaYK6dq1qzGpxNixY9WYy0mTJsmwYcNilJ88ebIKMFEO0O0LCR4wkbYeSFauXFnd4Msvv7S5bySnsKzAiYiIEoKr6lEiIiKvGiOJMThI3ID05XpFiOk/sAzZ+9DSWLZsWdViaAvSz2Psjp6oR4fn27dvt/oaJHywLI+xQQgmnz9/7tDfgPE+GGNUoEABad++vUpUERvM7fbgwQOzGxERkbvqUVPo2YP6DEFoxYoVZcuW2MdQYdwryqE8evHgQq0pTBmDMbFI2oTbq6++qpI6ERERxSmQREserpQi+EL6+aVLl6rsgm+99ZYUKlRIpZzv3LmzyvZnCybHRpKIbNmymS3H8xs3blh9DZZbK49KF9uzFxIEISMiWj9RWWK7NWrUUOnybUELKSp+/YbEEkRERO6qRy2HifTv318FowgAMUzk0qVLVsvrw0RQDuW//vprNU8ojkO3adMmlRF448aN6iIuegPhQu7Vq1f5hhMRkfOBJFLRo9JCVkAdHiMdPFLN4+rqhx9+KEePHn3htiy79miaFuvE1tbKW1seG1Sw6ApbunRpdZV15cqVavmvv/5q8zVfffWVhIaGGm+Y+oSIPJv+/UDex9ffO1fWo6bDRDDkA8M/cLETw0SsMR0mgvJ4HaaNwTAR3fz581UOgnLlykmxYsXURdeoqCg1xykR+Q5f/671ZZoHvHdOBZJoATxx4kSM5ViGVkZAd5nYgrvMmTOrBDeWrY9Ic2/Z6mh6BddaeYx3xHxpzkqVKpUKKtHd1ZZkyZKpOTJNb0TkmQICAozJt8g7YfiDLydCc0U9mpDDRPB/CesyZsxo81g4BITIe7Ce9H5h//3G0d9Lr0m206lTJ3X1E91hkNgGFR3GTgwdOlTefvtt4/gLZEa1JTAwUI3PWLdunUo6oMPz5s2bW30N5qtcsWKF2TLMXVmpUqU4nURUfuhGhG4+ROT9EHykT5/eOP9iypQpHeq1QO6Flq9bt26p9w0XCn2RK+rR+BomYjpHqA7J63LlyqV68cQ2BOTbb7+N9XiJyDOwnvTulsiwsDD1Gwe/ddx5wdWpGnrMmDGq0vnxxx/l5s2bahmeY7oNfTwHrnY2btw41u3069dPVaYIBBEkojsPxnT07NnT2J0U4zEwnhGwfPz48ep1mAIEV1XRPWjBggVmV2cxfYj+GK8/ePCgpE6dWmXBg08//VRef/111bUHb8IPP/ygkudgPAoR+QY9K7MeTJJ3QTdPfEf76gUAV9WjCTFMBMeIehbjJtFKagvqbNTPOtSrzCdA5LlYT3q39OnTu30GCqcCSUS+GNSPm5691LKrp7V5IC21a9dOJbj57rvv5Pr161KqVClZtWqV5MuXT63HMtNkAchIh/WoaCdMmKCyro4bN8449Qdcu3ZNypcvb3yOMR+41a1bV1WCcOXKFZVEAFdeMQdltWrVZOfOncb9EpH3ww9itKxkzZrV4azO5H7otWI6ftDXuKoeje9hIqg/0UqKeZfLlCkT67FgCAhuROQdWE96r4CAAI8Y+hHnPkNxHSuIwfy4WTN79uwYyxAQIl26Lfnz53/h4NOFCxc6caRE5I3wResJX7ZE8VGPxucwkZEjR6oeO8hwjnVE5JtYT5KznLrci2446JKKFkFcwdQ/gPwgEhERJWw9iu6k06dPl5kzZ6rx/ui1YzlMRB93CVh+8eJF9TqUx+swTATDPky7sw4YMECtwwVatGDi9ujRI769RETkfItkly5dVCU1cOBA1XXMV8ewEBERxQdX1qPxMUxk4sSJKs9A69atzfY1aNAgGTx4sNPHSkREiTyQ3Lp1q2zZskXNL0VERETurUddPUzkwoULLjkuIiLyXU51bUUWNk+YBJOIiMgbsR4lIqJEGUiOHTtWzSnFK5ZERESsR4mIKPFJ6ux4DEyEWahQITVhtGmWN7h7966rjo+IiMjnsB4lIqJEGUiiRZKIiIicw3qUiIgSZSDZuXNnm+tu3boVl+MhIiLyeaxHiYgoUY6RtITEO0gl3rJlS8mdO7crNklERJRosB4lIqJEFUieO3dOTVicN29eefPNN9V4yYULF7ru6IiIiHwY61EiIko0XVvDw8Nl8eLFMn36dNm5c6c0aNBATXZ88OBBNQkyETkpPFwkeXKePiIfx3qUiIgSXYskJjvOmTOnTJgwQdq0aSNXr16VFStWSJIkScTPzyW9ZCmxCguTRG36dJHUqUWGDHH3kRBRPGI9SkREvsKh6G/q1Kny/vvvy9q1a6VXr16SKVOm+Dsy8n0vvRT9+MIFSdQ+/1wkMlJkwAB3HwkRxSPWo0RElCgDyTlz5sju3bslR44cag6sv//+WyIiIuLv6Mi3pUzp7iPwHA8euPsIiCgBsB4ligem85dv2CDy/DlPM5GnBZIdO3aUdevWydGjR6VYsWKqVRJBZVRUlBw/fjz+jpKIiMgHsB4lige7d5s/37GDp5koATg1sDF//vzy7bffyoULF2Tu3LnSqlUreeutt9TUHx9//LHrj5KIiMiHsB4lcqGkFrkjnz3j6SXyxKytppBkp3Hjxup29+5d1WVn1qxZrjs6IiIiH8Z6lIiIEkWLZPXq1WXEiBESHBwcY13GjBmlT58+cujQIVceHxERkc9gPUpERIkykOzZs6dKtlOlShUpUqSIfPbZZ7JlyxbRNC3+jpCIiMhHsB4lIqJEGUh27txZlixZIrdv35axY8fKgwcPVPbWrFmzSpcuXeTPP/+UsMQ+HyAREZENrEeJEgBnFCDy3GQ7yZIlk6ZNm8qUKVPk2rVrahqQXLlyyTfffCOZM2eWZs2aybZt21x/tERERD6A9ShRPFqxgqeXyFMDSUtVq1aVIUOGyJEjR9Stfv36cv36dVdsmoiIyOexHiVyoTRpeDqJPDWQ3LNnj+zatSvGciy7d++e9O3bV1q3bm3XtiZOnCgFChSQ5MmTS8WKFdWYy9gEBQWpcihfsGBBmTx5stn6Y8eOqelIkFod2fDQBdcV+yUiInIVV9ajREREXhNI9urVSy5fvhxj+dWrV9U6ey1atEhleu3fv78cOHBAateuLU2aNJFLly5ZLX/+/HnVpRblUP7rr79W81Zi3KYOYzQRYA4fPlyyZ8/ukv0SERG5kqvqUSIiIq8KJI8fPy4VKlSIsbx8+fJqnb1Gjx4tXbt2lW7duknx4sVV62GePHlk0qRJVsuj9TFv3ryqHMrjde+++6789NNPxjKVK1eWkSNHSvv27dUYFFfsl4iIyJVcVY8SERF5XbKdmzdvxliOcZFJkya1axvPnj2Tffv2ScOGDc2W4/n27dutvmbHjh0xyjdq1Ej27t0rz58/j7f9wtOnT1WWWtMbERGRu+pRIiIirwskGzRoIF999ZWEhoYal92/f191NcU6e2AKkcjISMmWLZvZcjy/ceOG1ddgubXyERERanvxtV8YNmyYpEuXznhDCyYREZG76lEid/i973bJ4X9TZr7jwbklRowQWbXK3UdB5POcCiRHjRqlxnbky5dPXn75ZXVD4hoEYljnCCTEMaVpWoxlLypvbbmr96tX+PrN2tgWIiKihK5HiRJSr5+LyI2obNJ1dm3PPvGffebuIyDyeU71n8GckYcPH5b58+fLoUOHJEWKFPLOO+9Ihw4dJCAgwK5tYL5Jf3//GK2AISEhMVoLdUieY608ugFlypQp3vard0OyNeaSEofLu67JlE9OSftPckmpFi/F344GDRJp2hTzAcTfPojIrVxRjxK5w20ts3eceDt7qhGR85weiJEqVSrp0aOH0zsODAxU026sW7dOWrRoYVyO582bN7f6murVq8sKi0lm165dK5UqVbK74nVmv0TQu8Ul+fN6PVmy56wEP43Hc/LddyK//CJy9y5PPJEPi2s9SkRE5HVdW2Hu3LlSq1YtyZkzp1y8eFEtGzNmjPz11192b6Nfv34yffp0mTlzpgQHB6t5szAFR8+ePY3dSd9++21jeSzHvvA6lMfrZsyYIZ9++qlZMp2DBw+qGx4jlToenzlzxu79Elnz7/Xi6v7Es0Lxf4Lu3eObQOTjXFGPEhEReVUgiWkyEIxh7kVMnIzkNZAhQwY1lYa92rVrp8p/9913Uq5cOdm8ebOsWrVKjRnRs9eZzu2I8SNYv2nTJlX++++/l3HjxkmrVq2MZa5du6bSp+OG12NqEDzGVB/27peIiCg+uaoeJSIicpckmp6txgElSpSQoUOHyhtvvCFp0qRR4zsKFiwoR48elXr16tmdQdWbYfoPZG9F4p20adO6+3C8ExJK6K3Jx47hgyWeLF2SUHkg6dRjx//XvADS/f/3Q9LI5TvxcBgbim69ifFvp0T3/ZsY6lFfeJ8oJtO8hB7zVT1lCrqtmS/LmlXEyhQ73qxI4Hk5/byAZ517StTfv061SJ4/f1618llCMprHjx+74riIiIh8FutRIiLydk4FkuhiinGHllavXq2ushIRERHrUSIi8l1OZW397LPPpFevXhIeHq7mX9y9e7csWLBAhg0bppLYEBEREetRIiLyXU4FkpjrKiIiQj7//HMJCwuTjh07qjmxfv75Z2nfvr3rj5KIiMiHsB4lIqJEO/1H9+7dVbrykJAQuXHjhly+fFm6du3q2qOjxOO/1Pfu1LdCkLyWdY88vPbQbPngepukQaZ9xkQ7McyfL1KxosisWSKbN4vUqiVib/r+U6dE6tWLmWgnoa1bZzjuf/5x73EQJSKsR4mIKNEFkk+ePFEtkZA5c2b1HOnK165d6+rjo8TixAm37v7RjUcy9kBdWXWrsmyccNxs3bdB9WT93Yq2X4wJxffvF3n3XZEPPhDZtk2kbVv7djxypEhQkLgdjh3HbTJvKxHFH9aj5BWuXYvOfIoLvnfvisceJxF5RyDZvHlzmTNnjnp8//59qVKliowaNUotx9xYRE5Nf+FGURFRxscRzx3Mqf3fRRXl5EnD/bNn9r32zh3xCFeuGO5v3XL3kRAlCqxHyeOhPsiTRyRvXpGdO0Xy5xcpUkQ8TkhI9NRRtuYpISLPCST3798vtWvXVo8XL14s2bNnV91cEVyOGzfO1cdIRETkU1xdj06cOFFlVE+ePLlUrFhRtmzZEmv5oKAgVQ7lMX/l5MmTzdYfO3ZMWrVqJfnz55ckSZKoXkeUyOACY1SU4cKo3nPGUy5+WrsQaqlu3YQ+EqJEx6lAEt1aMYEyoDtry5Ytxc/PT6pVq6YqQiIiIkqYenTRokXSp08f6d+/vxw4cEAFqE2aNJFLly7ZnMOyadOmqhzKf/311/Lxxx/LkiVLzI4PAebw4cNVkEvkdTJlcvcREPk8pwLJwoULy7Jly1SCnTVr1kjDhg3VciTeSZs2rauPkYiIyKe4sh4dPXq0SnbXrVs3KV68uGo9zJMnj82hJmh9zJs3ryqH8njdu+++Kz/99JOxTOXKlWXkyJEqE3uyZMnsOo6nT5/KgwcPzG5EROS7nAokv/nmG/n0009Vl5eqVatK9erVjVdVy5cv7+pjJCIi8imuqkefPXsm+/btMwaiOjzfvn271dfs2LEjRvlGjRrJ3r175fnz5+IszCWdLl064w3BLBER+S6nAsnWrVurLjOodP4xmS6gfv36MmbMGFceHxERkc9xVT16+/ZtiYyMlGzZspktx3NMzWUNllsrj/mhsT1nffXVVxIaGmq8obWViIh8l0OBZM6cOeX999+X1atXS8aMGdVVU4zp0CF7a7FixeLjOImsCw936Mw8D3suEeERsZbRNE3C74fHyOYaY9f/lTETEWHf8WLeyBdd+UdZTTP/G/XXxfZ366+zBa9/0XE6A0kZnj41bNvV23fwfSbyVPFVjyIhjuX3mOWyF5W3ttwR6AKLbrmmN/IiqF9athR57bUX10//OfbXGamU6rj81GyTcdmJVeekcqrjMqJJ9DJ7Xdh6RaqmPioDa1t5LeYqx7zL9naZ/u03h/dPRPEYSP7222+SMmVKNSgf80e2adNG5s6dK3c9dV4h8mzz58ft9ZiCJnVqkcGD7Sr+8NpDKZDmthROfUPCbptM2WGh9U/VJVOGSNnz63F5KYX1K+r4rZU6Q1KZ1GGz7R1+8YX584EDDcc7c6ZIiRIiuXLFngEPiQLwAxM/xpYtM1TseF1goEiKFEj1GPM1+/YZXvf669a3ef++IZU7fqgi6HMV/AitVUskVSqRgACRggVFHj92fnum3ynvv284B6tWueRQidzJ1fUotuHv7x+j9RFjLS1bHXVInmOtfNKkSSUTE5QkXmfPivz5p+G79uhRu14y8pMbsi+shHy2sp5x2dhPr8jesBLy5T/Ry+w1e8AZ2f24lPyw1eK1oaGGuhPZY+2de5mfZSLPCiTr1aun5os8ffq0GmNRoUIFmTBhguTIkUOtQ3ecs/giIrJHXDMBfv214Qrqt9/aVfzslmtyNSqHXIzMLRd3Xo+1bJikkl9H3ZJzEflslomUpNJnYVXbG/nxR/PnP/xgON5u3UROnTLM0RUcHMtB/BfsIoAcMQL90QyvM92eJQSXeN3Klda3iddjO/h/aitlujNwjDt2GP4+QJe28+cd2wYCa92JE9GPMS0Btj96tIsOlsh9XF2PBgYGqmk81q1bZ7Ycz2vUqGH1NRiPaVkeYzMrVaokAbgQRImTaU+W2Hq1mLj/OObn5UGYv9OHYDotsxnT40HvF1uKFxeZPt3w2N/54yCieBwjCSVLllTjIXbu3KlSlXfs2FE2bNggpUuXllKlSslKWz9kiVzl0aN4PZf21KPPJFn8bNiStdZDa909ndm2p0iaNPb1mMuMyIe4qh7t16+fTJ8+XWbOnCnBwcHSt29fNf6yZ8+eaj328fbbbxvLYzn2h9ehPF43Y8YMlfzHNInPwYMH1Q2Pr169qh6fOXMmHs4EkYuguxCHWBElmBf8crMPusn06NFD3R4/fqyubNqbLpyIiCixi0s92q5dO7lz54589913cv36dRWErlq1SvLlM/SowDLTOSULFCig1iPgRGsoxm2OGzdOWrVqZSxz7do1s+yxmBoEt7p168qmTY6PfSMiIt/jVCC5f/9+1f0FV03hr7/+klmzZkmJEiVk8ODB0qJFC1cfJxERkc9wdT36wQcfqJs1s2fPjrEMASGOwRZMS6In4CEiInJZ19b33ntPTv03VuvcuXNqwmIkD/jjjz/k888/d2aTREREiQbrUd+ERG7j2wSpZG2JwYPwwHjbthalybz3t8ny/rvMVxw6ZBgzf/Wq4bmj4/GtZHOf3HGzBP18MNZyR/88LT+3DJLQS6Fx2h+RJPZAEkFkuXLl1GMEj3Xq1FGZ6HDVc8mSJa4+RiIiIp/CetQ3Te2+Rz5aXFfqdskvicHG+9Hdn10NU4t0mlxTmg+tKnfO3IteMWiQyCefiHTvbnj+1lvR6/I7ft6XD9or7y+oI/X6GH7X2tK0TUrp82ddGdb2gMP7IPJVTgWS6O4S9V/WrPXr10vTpk3V4zx58sRpMmMiIqLEgPWobzp+wjAP5xNJ6e5D8XqhN54YHz++YyW53OrVMRPPjRnj8H6unrMvkdvlSENm8R0n0ju8DyJf5VQgiRThP/zwg5r7KigoSF7D5LWqd8F5m/NW2TJx4kQ18D958uQqhfmWLVtiLY/9oRzKFyxYUCZjagALaBXFOBMkKsD9n5gXyQTGn2DSZdMbEh2Qhzp8OPZpMpxwaO1NNa/kuuH7ZP2P++VmcDzNhYq54XBxxdpUHYApQOxx7ZrI1q3my06ejJnN1XTuL0zFcfBg9JQhmIfr33+j12MurnPnRHbvjjkXpanTpw1Tmdy7Z8gKi2k+9C5FT55gngHbOdtxDKjsFy0ylLWEaT1wTDg20x8DSOaxfr1r57ok8iCurEeJ6D9FivBUEHl6sh3Mc/XWW2/JsmXLpH///lK4cGG1fPHixTbnrbJm0aJF0qdPHxVM1qxZU6ZMmSJNmjSR48ePS15Mmm4BFSxaP7t37y7z5s2Tbdu2qeQCWbJkMWabw7xcyGD3/fffq2QFCCLbtm0rW7dulapVq5qlXUdrqg4TOpMHwlyHZctGB2UZMrhksx1+qSHlpwfLgScV1fPsfjclXrz+usj27XHfzs2bIh07xlw+YIDIyJHRwabpdAHffx89x+aDByKtWxuCM13Xrtb3VamSyLFjIiVKGKbc0CvmYcNEFiwQadIEs6AbguA+fUSmThV5803r25o2TeT99w2Pe/QQmTLFfP3w4SLffCPSoIEhqNT172+4/+yzF5wYIu/kqnqUiIjIqwLJsmXLypEjR2IsHzlypCR90VxwJkaPHi1du3aVbpigXUTGjh0ra9askUmTJskw/Gi1gNZHBJgoB8WLF5e9e/eqlOR6IIl1DRo0UPNmAe5xtRfLF+BH8H9wnGyF9AI3bkQ/RsueiwJJOPCkePRuouKpBcAVQWRsJk2KDiQRbJrasyf6MVoTTYNIewJ4BJKmLY337xtah0Hvwo4gEubPt76df/6JfoyyloGk/jq0anboEPP1VnocEPkCV9WjREREXtW1FV1KMWeVpfDwcCliZ7cCTHC8b98+adiwodlyPN9u48c3Whstyzdq1EgFk8//a82wVcZym6dPn1ZzZ6FbLbLOIvtsbJ4+fSoPHjwwuxEREbmrHiVyCQxZeNEwi0eP7N7crYfJozcdpcmtYMOFx5Bjt+Tu2XtybtMltdwlcIEzNhhS8fCh9dehx42X0cQwBpfIqwPJCxcuSCTGPlkJtq6gJcMOSMqDbViOBcHzG6atUCaw3Fr5iIgIY5IfW2VMt4kurnPmzFGtn9OmTVPr0JXIWqWuQwtpunTpjDckFiIiInJXPUrkEu+9J5I1q8iHH9ouY2ucv4XFn+yQ9XcNQ0bgnSLbJGuJzFI44KJkK5VFMhXOIIVezisdC+xwxZGLxJbfAuPuCxUSyZFDJCQkejnyBuB1ZcqI/Jc40luceZ44sgGT93Co/8zy5cuNjxGEIaDSoUL8999/VQufI5DoxjKTneWyF5W3XP6ibWIcpg6TQVevXl0KFSokv/76q/Tr18/qftFF1nQdWiQZTBIRkbvrUaI4wVh2cGT4gw2/zEhh9vzXs7XU/dmIfGbLF16qIdGDjeLANCFb7tzm6zDcQ291PHPGECzD3r2G1yFhnWmSNyKK30DyjTfeUPcIyjp37my2LiAgQPLnzy+jRo2ya1uZM2dWCW4sWx9DQkJsZqzDmEZr5TGeJFOmTLGWiS0LXqpUqVRAie6utiADLG5ERETOcmU9SuRpojQ3dr20kluDiDyoayvmjsQNCW8QnOnPcUN3nJMnT0qzZs3s2lZgYKCaxmMdkmyYwHNbGevQcmhZfu3atSqNOirg2MrElgUPxx4cHCw50P2BiIgonriyHiUiInInp1LDYRoOV0BX0U6dOqlAEAHg1KlT5dKlS9KzZ09jd9KrV6+q8YyA5ePHj1evwxQgSKwzY8YMs2ysvXv3ljp16siIESOkefPm8tdff6lpPjD9h+7TTz+V119/3ViRYy4vdFW1vDpMREQUH1xVjxIREbmL0znGMY4DN/2KqqmZM2fatQ3M94gEN999951cv35dSpUqJatWrZJ8+Qx96bEMgaUO40awvm/fvjJhwgSVdXXcuHHGqT8ALY8LFy6UAQMGyMCBA9XYR8xXaTqHJBIZdOjQQSXowRyU1apVk507dxr3mygdOiSrW8+Q/RlflX6rG0iKjIZxDidXn5M5P1ySwECR9BmSyMeL60gSPwe7rvzxBzJLiPTta5gOY8MGw/yDpn75xTDQ33J87IoV9u0DE963a2e+v3795OLO6zKx3xm5dc9fwp+hAb6o3Yc98Whd8XiPHxvOWffuInXqmK9btSr6cZcujm9740bD9CKW81bqfvwx9tevXm17Hcbi7NhhPZueqResP7HqnMwbekm6Di0kBerYToD16MYjGfPmXqnWII00+DI6EUR8OfPvRZk96Lx0+baAFK6fiL9XKN7rUSIiIrfRnDB48GDNz89Pq1Klita8eXPtjTfeMLslBqGhocjyo+59QqFCmiEHuKbNfGezcXHVVEeMy3HbN++4Y9t98iT6xWvXalpAgOHxN99oWpMm0etwO3w45utN1586Zb4uXTrz9Y8eaVpYWPTz9eu1LoU3mxWJj1u878AdtzVr4r4NPz9Na97c4mRZeV/1W4cOsW+vdu0YH4+KKY+pVQ0y7o31Y/hL600xDiE+1U57UO2rVtqDCbPDRMYXvn8TQz3qC++Ttm+fpjVurGnLltlVvHuxoLh/1/Tvr2lt22ra48eG5598omkdO2paeLgWLxz4Xo+UJDZXp5X7jtWdFlYO3m22fuvEQ8bHF/85/uINzp1r2NDWrYbngYHR6/LkiT6f8+dHL3/0SPtZPrJ6TL/33a41zrxbO7LU8NtDL1Mn3YEYxx75PFLrVjRI61EsSIuKjIr1dO+aeVRrlGmPturb3XF6q4g84fvXqRbJyZMny+zZs1W3VPIRZ88aH167HJ2SftfjUmbFHt9zcN6l/+b3VEJDo58HB1tvXYsLZGfz9zfb3437nKbFbdCMHc/2hZVQ9+tM0s1bc/GCi+Yss9OWB2XV/db/7okssR71EsjWHhQk8s8/ht/v8Q3zNQ4ZYnj81lsi1aqJ6MmXME2HZc+TBHYyll49DyQ6A7EzXhtcWeLN5cuG99Eka7+C3ks2tB1TXd3799wtf7eIffPBK8/J9JOG96bvP+ekWNOCNsv2+jCJ7A2rJFsHPZJH34jT0NMmdfbUzm+AyF3zSD579izW5DVERETEetTrYc7BhGTaxRkXXk3nGrUy72hCixSTi7XexvTCtgPn9HxoxheWiXweZfWxNcfCDHNBPhbHg8AiAdFjq6MivGsOTPJNTgWS3bp1k99++831R0NERJQIsB4lIiJv51TX1vDwcJVhFdlQy5QpY5x6Qzd69GhXHR8REZHPYT1KRESJMpA8fPiwlCtXTj0+evSo2TpMskxERESsR4mIyHc5FUhuxLQARERE5BTWo24eK/fXXyKlS4sULRoz6RvWIalNeDjmIXvh5h5ceSArhh6RLHmSy18nixuXP3v0TBb03S3790TKd8vLSbq8/yWjuXULE2WLZM4s8uqrIk+fikREiLz+esyNI0mdNUj8gymesmUTqVQpejm2tWyZSOXKIgWtJHzZvVsEc3NjSrSUKUX+9z9xl9ndtkrhCmml1gdl5MndJyJimHZM1/ez6PGYPzTZKuMlQALFyjjH2BLwmZo1S2TcOMy7E73s449FpIzx6fg2QfIgVJOmXXMYpwsLflpQepcLEhHDlGCbQ8vJrhlHpWrX6GSEx4JuYwTjCw/p7tl78kQyRL/urzNyctttyZI3hYQ/ijBOT3X/YqisHHFUGn5UVNLmSiPLBu6TSs1zmW3r9Karcm7/MXnjh0oSkNK8ZyB5vojwCPlr4B4pUTerFG9WSBLdPJJEREREXmf+fJF33hHJlEnkNgIAEz/8IDJ8uCEQu3bNrs190eigTD4eM5vqgFe2y8g99dTjO3W3ybzzNQ0rEDwePmx4PGJE9As2bRIpX958I598Yn2ne/aINGtmePzkiUjy5IbH48eLfPqpIYg0ycauhIUZAkiYMMFwjzmI3eSdGbVEZojcbnBXxvfA+TCcK92exyWNj6dp3aWC7JOeMsX5HSLAtoRMriaB5EeLDcFi/3XRRTTxk3GHzOeVrtatlDx8LTprasfx9iWg/OBlZKyPLlv5jZzyRAobn58sf16KNCogfV89LLPP1JbXluyWBjWfSJ8/60r+iZclMEl0gp3anfLJEykuU0I2S4957s3mS45b2HeXdJpcU9L9FKomzklUyXZefvlleeWVV2zeyL1WDNwttdIelk1jD8rjkMdqvnrciiU7J/9v7zzgo6i2P/5LT0iDUEMLoQXpRZAOglJsKCKggKBY8ClN/yICCsrzoSjlSRdR8YmgVJEqCIl0CAklEEILJLSEEBLS6/w/5w6zfTe7m91sFs7385lkym1z9849c+aee+7jLntxqUYX4MUX5ZPKpsHBk74ifmNPtXcwhafHhiLjxv1F4iMjgaAgOf7y5cCdO0C/fvKXVnJfTl97AwLUkV96Sb2/dq3+gvVTpmgfT5wo/hXDBa9iJQZ3iBdfcIRwfPxx/S+1tMC9Bju/T8SOFDu6E3+Q6du39GnQ13zdZV6oTRhz1LV6ten09u0D7t2TX/z69sXvweO1LlMznNwxXHiyGx56AEPrHkRRvuyR75tI9QtKQbbhL9rbPz8m2v3u2VGqc1/1D0fvoCgkHLquOjfn2XCRV7sKsWLEwZ5M7yHnVcvtpkkPfX/NOq56lM/v1H9uzYXqi+qtvkcCugScwroPtJ+p0rLzi0hRx1ReBapvOkf1/zDBctSBnDwp/yeZpcuWLWpF7br6uTfF6rOGl/k5e7WCan/VlftKJKEokbrQSKUuW7caDnvrlnZfq3DggPz/8mX9OKRI6qIrhx1AWmIGdh0v2TNqJDRGXssBmckG6rMEfkvUVjhzoG4jRMqVTPGflEhia3IHHIyURxuvFNYxGPe4ujtlnIiYaPldJL2Uy+Y45YikMj9SoaCgACdOnBDzJUeOHGmrsjFW8sq/H0Em/PHWpHgsyKIXebnzjcuvjzjUx7dJg/HfDROMxt9227jylYEA/L3gCJ6f9RgwaRJw96584a23AHd3YOdOebMGMpkmV9y0FiStpTV/vjh9GfXxP7wKpAEfbzyHNocWy19udRk/XqtH/Wy7bZVIFxSLL5NMKVzn05zqYcOsr8Jdu+SXv7/+whDot7OvjvTEiK0XVS9tUzafR8tB2uZGpzZcRLvhavMzhVdnhCJFqoLRU67h6iT53OQdsgK6fFI4Zu6TzYr+b4t8LirnEUStiRFfpu3F5//Ied0oDkbcjktGzV9GTVObPM2ZkIhlsaFW5Xf2z0uqF534jLo4OBeQ7i9hZwtGfVoHt4qrY9S0W7jxsXxu9JRqSCiqjeEzUnGnFGuqORssRxmGYRhnxypFct68eQbPz5gxA5mkADAOhZRI4kJBKIoKdcx2ANzVsM+3hsL8+yMjCQnaF2huhh3W0irWUN6KiyS18qqLjhlPxv16sAXbZ0aiae9ghHTWnqNglM8/l02Uxowx+6u2nulVaRSuB3luk+bXdwNoruEl2osOhs4RpEQSpNTokpFp2ImYsbTsgam8bhbXUO3fybB+roy974eUSN3yKvWdKpU8IvEgwXKUYRiGcXZsOrwyfPhw/PDDD7ZMkmHKBf2mPYq6ncxUIomnn5bnrwwfbl2GAwZYF49hGKeG5SjDMAzzUCqShw4dgrcy4ZthGIZhGJaj5d3KgTZlDiF5Qy0JsoqgOORptaAABUaMuyRJ25KB5meTd1KjOdDUDnKco1k2Teiacl3zGp2jslC5NMtPYehY8x51MXa+DMnNKEBBseOmjWhaPVlCQU6hyXn3ynmaS5+blmvWnPqC3CKj6RmNU+QCqVi7VZE/CSU/ylu0u2JJpG2qvLTl3cszOCef5tArfgdMlud+OrSVdN8l3as5dUFhdO/fERQXFst+PCyoKwXN8peX+7GraevAgQO1jiVJws2bNxEZGYlPPvnEVmVjGIZhmAcSlqPlBE9Py8KPHg1oWF6dREtk477znhL8DXj6ktk5bZJwIqdnMD90qOljsnQxRM2a5t3b22/rh0lKgqNp/rzaa2mpIGXaQvLgiYmQ/TFYSt2ONeGBfBRAvw198WQ4Pt/dCZ0rRiM8TccTrwl6TmgNGHdhgfMF+vPff7zQDfGVo7HnTmu4uLrg6oFrqNdVnjLQq1IU9txtqxFanvoQs+kimg1Q1/vIBvvx8+WuquPWPucQmdYIbp7yEizkuLF5rVS4oRink6rBJ0h7qRaFqFWxOj4I5PxeCTmg7XAKwHstI7DidAf88Z9T6POxvOyJJi+HHMSWhBbY89MFtB/Z1Gh+PYbXRv/aMfg9sRMcqUR2CDyHhJyqOBKeiyd6F4sPFDHXg+BbzbfE+E9UicbulDZiOZguA6uhe7U4/JnUAc6AVZ9hAgMDtbagoCD07NkT27Ztw/Tp021fSoZhGIZ5gGA56qToTN9ZCw1v5BaQhZJfLm3OslIsnVEOaACd5UzM8XpbAonQ9oRqKYaUSGLa7p7Ih5dFSmRpoHyUEbB9v1xVnddWItVsWnhN61hTiSRO5DRByvlU1fHF8GvCa+ylwhDE7zfu9+HXeYY/TPx6VVuJJBad7oFc+GDeXMMeydckdBY+P1bOMf67rpqXJMKsveY4JZK4G5+G49lNcVuqig1fX8LlwhC5vv4xz0cG/U40Crlx4XXcQyC2JDuHEmn1iOSPtKgrwzAMwzBWwXL0wcBas8gHndTLaVj5/klM3KRef7GiSxouxBahapPKVqXpAw2zX6ZUmGPBbQ3WWGTmFZpWRYqKXIznV2z8mjMiOY9Fa+kUSYXjx48jNjYWLi4uaNq0KdroLqTLWAzZk3tXtGyeKX3FSE+8By9/T3gFeGkPNBvwpJqNCsiFF7xhnZfV3OxiIC1Nns+hdcG0N02zIK+/Xl5y+gZIT8pFblYRvI09gRpeg3MNh2KcGWoXRtqGQuYddbu+ez0b2Sm01pd6ra6ce/LcjcykLHEcUMtfPHfQGCGgOO7e1D3KX5vTM12F6Yo810PdrrLu5ot1VV3dXcVzm3kr8348dVrqeBBhKC9PP08RL7Cu9vpRdI2eYQovz1Hx0ZpHdO/aPZEX5aGkJaPd1tMT0oVJUmFeEQLrBKjmZlEcSpe+XNP8ngqVfeRwuYX3+w59aL4MXVPmfFB8zT6KrlN5lHune6M+idJVzKIIuQ60v97L5fc2qw+kNCkvMt0ytaams8FylHkQITNeWhFMEw+aTeptoSkxwzDlGqs+pSUnJ6NXr15o3749xo0bh/feew/t2rVD7969cdsK0wJG5r8DI+BXyR3zX4iwqErqeNxCpXqB8kuhh/ZPOnFWVb3w6zEIPsjF7xomOVPxb7PzG7G0C2IrdQKuXNG+MHFi6X/KihUBHx8gJMTg5d7/1wY+G3/FaujMHVGoJXtW3YueuIhGcAr8/BxdAufhnXeAEsznu4xpodrv9UEb+FbVXvC5x7hW4iUnqH5Fsbl7ucGvuraZGcWhDzMKtDg0PVs+lbQVHJrXQYooxad0KoYE6qWlxKNtUodw8YzTOQrbLVA9typ8/glUrAR08I+Fd6CXeJ41eXTEI0Ip9A/2E2k95hejSleT9dc7ibQpHPULj/jEi3uhc0q6dI3unY49fNwRUMkVvSqfMFif1QJzEbvlEpr5XxXpUH40t4VIOHQdNSrmaN071a23vzvaBV5UmVrdOpUMX3/tL8dTOofrlX1cK7kP/N+Y/XrleLXhARGeylypsvOPArEcZRiGYZwdq6Tx2LFjce/ePZw5cwapqam4e/cuYmJixDlSLBnrmLCxB4rgrmUKYg7Xi4MNng/GDZxHmNF4M6F2jBQBy/KMhg1Hn9trOyQwh+n4zOT1pRgDW+CCYnzeK9zo9VYw8PLt4gKEGa93PVau1HeKUEFb+WEeDL4+1lM84wr777VS7S+bl408eCMy27BTAV2OZjU3K1xcfn2z5vkYm8tD8zV+/SpRKx2a20IcWZuANKmiXhwJrjiZGyYsJYgzO6+h8L7TBYVZh3rqxVtwSu4Dp36v71Dil3jtOTzODstRhmEY5qFUJHfs2IElS5bgkUfUnpnItHXRokXYvn27LcvHlIIwxJm8nqNhNucwGjWiBmVxNDLPNUWhmVbbivtuTbJuZ4tF7Wlx9sIC4JO/9V94FZrirP7JuDjA10xHCmQeTF6Qdc2CSRlVoBFa8kZHYWn78EPz0jY3f4Xaspc3Pb7+2vJ0rfHeXLmy0zuDKA1FD9hcD1MEIt3k9azictA32RmWo5Zzat150TV2DThllmv965E38Xrjfdg89Yh8gqxoRo0C5lvnpdOiD4Ql8BnYMaGlHIVzOCBp/bxhiypr+T2xs1nhyLqEng+yGisJeq95oeZheLrka71uaPJUhxT8q/k/aFPhHLoOUXsGvhyZKuLQ9uu7B8QzphzPizL+vkRWKG0rxKK2202tPPemtcGmj+VndPvnx/Bao33C86zC/862Fc/yczWOoLrrbfw2/qA4fyPqFuZHqwdB9s6NxqiG+xG3/bJczvAEcfzXrOPi+Mt+4RhU+5DIO8j1LgbXkfeH1D2ICW0i8FX/cJzdfFGca1chVrX0CKU3rN4BLB4qW+LEbLwgwnT0ixHTQsjRztuPq9+3/29LT63lXCa2jRB1OLTuQRxcdlrUKdX7V0eM1xUxov5+PF4pWuQ159lwjG0ZgQWDjFss/vnJURF2YM3DYhpImSFZgZ+fnxQdHa13PioqSvL395ceBtLT02lKrPhvK+RJfvJmbTzNrSf2GL1GWwNcUB10wT6TYXW3VXjZ/MCmtrAwSbpzx2SYODTSO10LiSbjDMQ6s7IvKijSO5ebnmt2Xb+MVfonL1xQR/joI9MFMNUAlP0KFbTDlZSmJZtmPnXqGA4zZ47l6X76qeVxqlWTpOXLzQ5vqypw9KbwUu2DDi/Lid/OGTw/reteg+X+faLpMt+5mCrC7Z59XOt8INJMxgtyuVPCs2f7/reseRjkqK3lZKj7VVUbOPz96RLD/6t5uPZzNmKEzR+ar/Ch1dFvo7LjOyBzNj8/1f5pNDMrSn5WvrRgkLr+aWvvGyPkq7XF6IXdpgP88Yf8O8fFmZ3oBTRwePU629bM67xd0iWU/Vfra7+Taj7LStiJbbXlUsB9ufJU1aPi+uA6B8SxO/KlpJhks8pQzz1Btb9nTpRIZ0zTCK123dTrgup4/+KT0pzn9OWjsuk+AyW9j857vuTwOXdzDPZ3mmF2/PuYXfQUQ1g1IknzI8ePH48bN26ozl2/fh0TJ04U8yQZhmEYhmE5akviC+uq9vNzSh6RjE+qoG8tYmMq4a7eudcb7TMrbr6RpSPKDWPGADNnAnv2GLz863sHsX1mJPbMicbzwYdV50/8FgePCtqm7DN6hmPdropGnXqZ4vNp8uhKhbpVgZgYYPlyYO5c4JdfgKlTgX/9C1i8GHjmGTlC48bA77+bTvS11ywuByNzJs/+/ifikiqafpZpjn6Sl940DOLkHdm66myy7COEplXkZ5u3xigt2aGQly33MZk5alWJHL2dzWuo1Q/dTjaeXn6+ZW5YAyuVrJaZY42Rk1lyGId6bV24cCEGDBiAevXqoU6dOsJra0JCAlq0aIFf6MFmGIZhGIbl6EPIivPdsM0tCbeKq9smwUGDgHXrzAv7xBPA7t2lz3PoUGDJEnk/JUV9vnoNIAmohiS8vEBtcnlsdzg23ZT3Ww3WNwH+9O8ewuOyNdQKva8wtGwJNAPQjP6UwEslrO85diyQnQ38Fql3qbprMgolN9yRrFumhGEeJqwakSTlMSoqClu3bsWECROEg51t27YJN+a1jc2zMsLixYsRGhoKb29v4fl13z7TX/IiIiJEOApfv359LF26VC/M+vXrxZxNLy8v8X/jxo2lzpdhGIZhbIUt5agjZSnDMAzz8GKRIrlnzx4hTMg7K/Hkk08Kz3MkAGkpkGbNmlmkkP32229CgE6dOhXR0dHo1q0b+vfvL0Y3DREfH4+nnnpKhKPwU6ZMEXmTsFM4dOgQhgwZghEjRuDkyZPi/+DBg3HkyBGr82UYhmEYW2BrOepIWcowDMM83Fhk2jp//ny8+eabCAgI0LsWGBiIt99+G3PnzhXCyRwo7OjRo/HGG2+o0t+5c6fwCDtr1iy98PTFtG7duiIcQV5jIyMj8c033+DFF19UpUGC+eOPPxbH9J++vNL51atXW5WvvaC11Q7+InuXkumo2tswST3foGTU8TRJgHo+iSEuoSE24AWxn4IqFntP84aOp1FryKgF/ElzKeRyGOIG1N7CFK6jtqrshoiBeUsjlJZE1NEvx05f4NT9/TgywTFeTmzQPHhB5/z940Iv7XAlpWkJmvlkUxvQMGFSONXQ8vxiH7E8Tm4gEFXPdvfmJCjPekxyNUcXBX+vIts0fbO0Uxd9DJb7YHi+yfT+/PIM/Cu549RR7b4iX2cpEF1SpSADfaDhfs7ZsLUcdaQsLQvO74xHzN9Jem0gYtNd3E4wLSfPpqpHdkV7Ok1zu+S1hm1FFNpaHXcbnkIQUksOeJ28lZo55ymZlhTyR6lJbK+WO/c8Vf1yQp56yaKy5uZNYIOWzCwJE7Lk70DgWnvcBJuvlhfkPl9+xs9lqecqEmdTg/XCxtyubnRJPLp+Pk+9pNW2/14Qi+JZwv4dmci+dxiXbstzL4lNn5AHWLVJ9z9/piPqgvG1wE+dMV/N2vDRERyPLC4x3B+fnYC3r5uBK+r+8cDuHGRmH0OZYIlnnrp160pnz541ej02NlaqQ54fzSAvL09yc3OTNmzYoHV+3LhxUvfu3Q3G6datm7iuCcV3d3eX8vPzxTHlP3fuXK0wdExltzZfIjc3V3g+UrbExMRSe0PaPvOYw71vPewbecnS9UCWl5Fn9DdzdHl54zrgNuDcXlttKUcdKUvLSk5+/bRxj4jlcfOHfK89AqMdXhZ7bjVxTet3WjREx0OuJEkrRv2jOldcVKw6b2leK1eW7b3Rb9c14ITF8cg7qKN/F964DlDGctKiEcmkpCR4eBj/kuzu7o7bt2+blVZKSgqKiopQvbr2FwU6vnXrlsE4dN5Q+MLCQpFecHCw0TBKmtbkS9BX3c8++wy2pGINb3TxV4augFs5gbhUGIL67lcR7GN6nTVNDmS0VO1XcUlBiiSPLnbBfpxFU9xFEDr4n4UHClFY7IqbWf5IQAhaIxq+yFLFPefyCEJ9klQLoldzuY1kSfZ61cYnFtE56nVDKW0VlasAmRlAnoXr1tAX+Ro1gKrVgNhYIPWO0aDH0B75UHvoaoUT8EMm4O4BsdijDkVww2F00jrX3vcM/D3z8HS3ezgc5YW2zfLg6t4Ty7/NxaQPT+JcRi2M7xUDTz/ja/usff8QXprbCUFuaWjVvAj58deB7BwgOFi+fzdXoD4t3H7fqUBBPnDpEuDvD2Rmyk4L6H6Li+T7r6nxdTzlNjVyoGZNIKgykJwEJCcDtWoBlYLU4XKyyTYNSL8npxMYKK8zmZUF1AgG7qTI60M2aQLk5ADXrgNenkC1asDdu4C3t7xuJc3DCggErl8DMjKBevWA45HqNR2VZz00FDh6DCgy4vWsZSv5t7txU10eWmP2/HkgNVXOh+7n1EnteK5ucjVRWb28gUeayGU7TKZzkpy/q6tcr/S8JimjEjIX0RBJqIHySAP3q+JZ1qW51wXEaHi880YO2vnTl1KgSHLB4cwW8ESeqq0Hu97CzWLD9+iLTGRB/0toR7/TIh2Feu6JWp7oTEH90cGM5pB0Zj3Qec1+JgDpaOF/VexrnjeUnoISzg8ZaOUfj/OZwbh9v39RqOEqOyihegr0zNG6djSjCQrKu5fLMpajjpSlZSUna4V6qtpRSp4f4vLr67UtY5C8O5LVHD7IRlv/i4BULPfDpYH6TOqzstTpeCIfTbtVxpnTxXjvDRp974T5y3zQZqh8PdQ9AdcKa+i1XyFHSTa4uQPeXkBBgSwXqH9X8PUD6ofKfXzsOblv1CtTAECm0tRftmkj9/Mpd4B7Bt4jqO3R2sT5+drrF1MaHp5yeSgeyTHqlxWuXpH74rp1Rfle7U/WK2r5NfSLlti7/xAea03vAbIMHTijJXbsPoR2zfPg4qqWq+s/PIwfVrrCzVXC5luPaRWvf9VjeLJzFhZuDYW3WwFmjktBt/4dxXLLOiKgZDLuAYmJsgy9nQIk3VI7DGrYQL6fy5eFfGrexgPL1spydt4Sb0jFEj4cG4VjdxsiA7L1wOKh/6BmqBeenyWX+ZWQA7iX44EtyfL6llv/cwrLFhZgww3j1hNtfWJRJLniZG4YHvONQUaht5YXUEvpHngC/6S31jpHfWzm/VHp1j7ncCKniUVpar5H6uKOArT0uYio+++D9GzllLCutzkoMuV0RojwvvpohbOqd1GC6oqeZQV6/hWZqVDV5baQKa284+DnkYecQg9Rzkoud9HUL1FPVmnKWkMyWld+kROmhr63kJrni9j8BqowEoCDRuSgruzsLGRsS4Ny281FKlGm6pZLk+iMBsiGrypMoZSJI6Xs7szBIkWyVq1aOH36NBo2NNzoT506JQSQJZDHV03oY5XuuZLC6543J01L8yWznvfff191TPNbyFlCaej4RnPsly2RdCjNYraaD39XjX31A6lGPeyvRtPMQ/MlT61E6qdtC3TTLwntjtM8DHt66/RWC+x7SzkyvUDsoDmdIM2hPcU1dUlmMZ4W3FtVnTqnlzhDphvUaZvyWid3cGo0Tbn0zYSB2mb8riWZFZLQIrNUmGhz5rYZY4sp29/luO0IMfMeyGRUV2hoCjZTirIxcxq1YJWxpJ9qaeZ5MvVpaWV6/ibiVjfrt6Z3Zvpe4YzYQ446UpbaW06SZ9CXFxi6Yk770+wzLQlfeloPCYM0RDkyNs3EWJ9ozPy25IXm1f2Kob7eXAzlX8/k+0RQg0pYe037423FkED8nqh9jhg4uyMGzjaWd3vxd6LqWH5ONKbvWkCAhqwkma37zHlr3Yva3ZSseP09TDe97uKv9B9jv0c79JEtwU2g+T5giyk4ht6FNE2bLVMiZUxNdfLQuYfSK5GGZYpuG9OtK0PPs/L+pDs9o9L9TRdDS9E0MpEHTT/RnYLS0kAapq63NFNuW5Km4TDU/5aFnLTI2Q5Nzv/000+Rq/kV6z45OTmYPn06nlHW8SmBKlWqwM3NTe/rZnJyst5XUIUaNWoYDE9fcCvTCIqJMEqa1uRLkNc6mtOiuTEMwzCMo+SoI2WpIVhOMgzDPFxYpEhOmzYNqampaNy4MWbPno0//vgDmzdvxldffYWwsDBxjbzGmYOnp6dwPb5r1y6t83TcubN6IqsmnTp10gv/119/4dFHH1WZChkLo6RpTb4MwzAMYwtsKUcdKUsZhmEYxiJnO8SVK1ek/v37S66urpKLi4vYaJ/OxcfHW5TWmjVrJA8PD2nFihXC+cCECRMkX19fkQcxefJkacSIEarwly9flipUqCBNnDhRhKd4FH/dunWqMAcOHBCOB7788kvhtID+kwOBw4cPm52vOdDkVWd19sAwDOPMOHv/a0s56khZ+qD/TgzDMM5Kehn1vxYrkgqpqanS0aNHpSNHjoh9a1m0aJEUEhIieXp6Sm3btpUiIiJU10aOHCn16NFDK3x4eLjUpk0bEb5evXrSkiVL9NJcu3atFBYWJgRjkyZNpPXr11uUrzmwgGQYhnEMD0r/ays56khZ+jD8TgzDMM5Gehn1vy70hwdmLSc9PR0VK1ZEYmIiz5dkGIYpQxQnLmlpaWLtRaZ8wnKSYRjmwZaTFnltZdTcuSMvVVFaj3QMwzCM9f0wK5LlF5aTDMMwD7acZEXSSoKC5PWGEhISnOJFRvky4SwjqFxerl9uD/y8mRrpqlu3rqofZsonLCftC8tJrl9uD2WHsz1v6WUkJ1mRtBJXWviXVr4JDHSKBqXgbEuXcHm5frk98PNWUj/MlE9YTpYNLCe5frk9lB3O9ry52llOshRmGIZhGIZhGIZhLIIVSYZhGIZhGIZhGMYiWJG0Ei8vL0yfPl38dwa4vFy/3B74eeP+gWG5w3LSUfB7CNcvt4cH73nj5T8YhmEYhmEYhmEYi+ARSYZhGIZhGIZhGMYiWJFkGIZhGIZhGIZhLIIVSYZhGIZhGIZhGMYiWJFkGIZhGIZhGIZhLIIVSRMsXrwYoaGh8Pb2Rrt27bBv3z6TlRkRESHCUfj69etj6dKlKAtmzZqF9u3bw9/fH9WqVcPzzz+PuLg4k3HCw8Ph4uKit507d87u5Z0xY4ZevjVq1CiXdUvUq1fPYF29++675aJu//nnHzz77LOoWbOmyGfTpk1a1yVJEnVO1318fNCzZ0+cOXOmxHTXr1+Ppk2bCo9f9H/jxo12L29BQQE++ugjtGjRAr6+viLMq6++ihs3bphM86effjJY57m5uXYtLzFq1Ci9fDt27Fgu65cwVE+0ff311w6pX3P6r/LWhhk1LCftA8tJ28JykuWkJe2B5aT5sCJphN9++w0TJkzA1KlTER0djW7duqF///5ISEgwGD4+Ph5PPfWUCEfhp0yZgnHjxokXGXtDShYpNYcPH8auXbtQWFiIPn36ICsrq8S49MJ28+ZN1daoUSOUBc2aNdPK9/Tp00bDOrJuiWPHjmmVleqYeOmll8pF3dLv3KpVKyxcuNDg9dmzZ2Pu3LniOt0LKe1PPvkkMjIyjKZ56NAhDBkyBCNGjMDJkyfF/8GDB+PIkSN2LW92djaioqLwySefiP8bNmzA+fPn8dxzz5WYbkBAgFZ900YfHuxZXoV+/fpp5btt2zaTaTqqfgndOvrhhx+E0HzxxRcdUr/m9F/lrQ0zMiwn7QvLSdvBclKG5aR57YHl5BHzHy6JMUiHDh2kMWPGaJ1r0qSJNHnyZIPhJ02aJK5r8vbbb0sdO3Ys8xpOTk6W6KeNiIgwGmbv3r0izN27d6WyZvr06VKrVq3MDl+e6pYYP3681KBBA6m4uLjc1S3lu3HjRtUxlbFGjRrSl19+qTqXm5srBQYGSkuXLjWazuDBg6V+/fppnevbt680dOhQu5bXEEePHhXhrl69ajTMjz/+KO7J3hgq78iRI6UBAwZYlE55ql8qe69evUyGKav6NdR/lfc2/DDDctJ+sJy0Hywn7QvLyYdLTvKIpAHy8/Nx/Phx8VVcEzo+ePCg0a/fuuH79u2LyMhIYa5XlqSnp4v/QUFBJYZt06YNgoOD0bt3b+zduxdlxYULF4RJAZkODx06FJcvXzYatjzVLbWNX375Ba+//roYxSmPdas7mnvr1i2t+iMzvx49ehhty6bq3FQce7ZnquuKFSuaDJeZmYmQkBDUrl0bzzzzjBi9LivInJnMMhs3bow333wTycnJJsOXl/pNSkrC1q1bMXr06BLDllX96vZfD0IbfhBhOWl/WE6WDQ9CH8Ny0n6wnDQNK5IGSElJQVFREapXr651no6pszEEnTcUnsy0KL2ygj4Gvf/+++jatSuaN29uNBwpON99950wDyXzwbCwMKHwkN24vXnsscfw888/Y+fOnVi+fLmou86dO+POnTvlum4JsqNPS0sT8+LKY93qorRXS9qyEs/SOPaA5uBNnjwZr7zyijDJMUaTJk3EPL7Nmzdj9erVwuSyS5cu4kXM3pDJ+6pVq7Bnzx7MmTNHmF726tULeXl55b5+V65cKeYmDhw40GS4sqpfQ/2Xs7fhBxWWk/aF5WTZ4ex9DMtJ+8Jy0jTuJVx/qNEdcaKXHFOjUIbCGzpvT9577z2cOnUK+/fvNxmOlBvaFDp16oTExER888036N69u91fvBXIqQrl3aBBA/Gw0ktkea1bYsWKFaL8NJpaHuvWVm3Z2ji2hEababS6uLhYOPQwBTm30XRwQ0pO27ZtsWDBAnz77bd2LSfNw1Mg5efRRx8VI3c00mdKQXN0/RI0P3LYsGElznUsq/o11X85Yxt+GGA5aR9YTpY9ztjHsJy0PywnTcMjkgaoUqUK3Nzc9L4qkbma7tcnBXL+YCi8u7s7KleujLJg7NixYsSAzCjJ/MxS6EWxLEZwdCHvnKRQGsu7PNQtcfXqVezevRtvvPGG09St4g3XkrasxLM0jq2FIzlGIZMjcsBiajTSEK6ursITqCPqnEakSZE0lbej65cgL9TkEMqa9myP+jXWfzlrG37QYTlZtrCctB/O2sewnLQ/LCdLhhVJA3h6eoqlJhTvnAp0TCaYhqBRJ93wf/31lxid8PDwgD2hL2D0JZ/MKMm8juYdWgPNeaKX4LKGTABjY2ON5u3IutXkxx9/FPPgnn76aaepW2oLJOw064/mNpGnTGNt2VSdm4pja+FISgop7tZ8LKBn4sSJEw6pczLRphFoU3k7sn41R9epnyPPdY6s35L6L2dsww8DLCfLFpaT9sMZ+xiWk2UDy0kzsMpd0EPAmjVrJA8PD2nFihXS2bNnpQkTJki+vr7SlStXxHXy3jpixAhV+MuXL0sVKlSQJk6cKMJTPIq/bt06u5f1nXfeEZ6ZwsPDpZs3b6q27OxsVRjd8s6bN094czx//rwUExMjrlNzWL9+vd3L+8EHH4iyUp0dPnxYeuaZZyR/f/9yWbcKRUVFUt26daWPPvpI75qj6zYjI0OKjo4WG+Uzd+5csa94OSUvXtQ+NmzYIJ0+fVp6+eWXpeDgYOnevXuqNKj8mh6JDxw4ILm5uYm4sbGx4r+7u7v4vexZ3oKCAum5556TateuLZ04cUKrPefl5Rkt74wZM6QdO3ZIly5dEmm99tprorxHjhyxa3npGrXngwcPSvHx8cJjb6dOnaRatWqVy/pVSE9PF8/UkiVLDKZRlvVrTv9V3towI8Ny0n6wnLQtLCdZTlrSHgiWk+bBiqQJFi1aJIWEhEienp5S27ZttZbTIJf/PXr00ApPL0Jt2rQR4evVq2f0Jc3W0ENgaCOX/cbK+9VXX4klLLy9vaVKlSpJXbt2lbZu3Vom5R0yZIh4CSRlsGbNmtLAgQOlM2fOGC2rI+tWYefOnaJO4+Li9K45um6V5UZ0NyqX4haaXMmTa2gvLy+pe/fu4mVcEyq/El5h7dq1UlhYmPidaPkVWynCpspLypix9kzxjJWXPvSQok/to2rVqlKfPn2Ecmfv8pKyQ3lRnlRPVAY6n5CQUC7rV2HZsmWSj4+PlJaWZjCNsqxfc/qv8taGGTUsJ+0Dy0nbwnKS5aQl7YFgOWkeLvTHnJFLhmEYhmEYhmEYhiF4jiTDMAzDMAzDMAxjEaxIMgzDMAzDMAzDMBbBiiTDMAzDMAzDMAxjEaxIMgzDMAzDMAzDMBbBiiTDMAzDMAzDMAxjEaxIMgzDMAzDMAzDMBbBiiTDMAzDMAzDMAxjEaxIMgzDMAzDMAzDMBbBiiTD2JAZM2agdevW5aZOXVxcsGnTJovjxcXFoUaNGsjIyLBLuZyZ5ORkVK1aFdevX3d0URiGYZwOlpMPPiwnHx5YkWScjqVLl8Lf3x+FhYWqc5mZmfDw8EC3bt20wu7bt08oU+fPn8eDjK0F89SpU/Huu++KetYlLCwMnp6eDlGkrly5In7PEydOwFFUq1YNI0aMwPTp0x1WBoZhGFOwnNSH5WTZwXLy4YEVScbpePzxx4XiGBkZqaUw0gjasWPHkJ2drTofHh6OmjVronHjxg4qrfNx7do1bN68Ga+99pretf379yM3NxcvvfQSfvrpJ5RX8vPz7Zo+1c2qVatw9+5du+bDMAxjDSwn7QvLyZJhOflwwIok43TQiBgph6QkKtD+gAED0KBBAxw8eFDrPAlU4pdffsGjjz4qRtlI6XzllVeE+QVRXFyM2rVri6+4mkRFRYkRsMuXL4vj9PR0vPXWW+JrW0BAAHr16oWTJ0+aLO+PP/6IRx55BN7e3mjSpAkWL16sN8K2YcMGUc4KFSqgVatWOHTokFYay5cvR506dcT1F154AXPnzkXFihXFNVLoPvvsM1EOSos2TSUvJSVFxKG4jRo1EkqiKX7//XdRBqoPXVasWCHqjUbkfvjhB0iSpHW9Xr16+M9//oPXX39d1HPdunXx3XffaYWh34dGT6k+6Pcg01vNUUZSzoYNGybMR318fESZqQ6J0NBQ8b9NmzYiTs+ePcXxqFGj8Pzzz2PWrFlaHw5Onz4tfiNKp3LlyuK3o48QCko8KnP16tVFnVJd0mj3hx9+iKCgIFEPdK+atGjRQrShjRs3mqxLhmEYR8BykuUky0mmTJAYxgl55ZVXpD59+qiO27dvL61du1Z65513pClTpohzeXl5ko+Pj/T999+L4xUrVkjbtm2TLl26JB06dEjq2LGj1L9/f1UaH3zwgdS1a1etfOhcp06dxH5xcbHUpUsX6dlnn5WOHTsmnT9/XlyvXLmydOfOHRFm+vTpUqtWrVTxv/vuOyk4OFhav369dPnyZfE/KChI+umnn8T1+Ph40sSkJk2aSFu2bJHi4uKkQYMGSSEhIVJBQYEIs3//fsnV1VX6+uuvxfVFixaJNAIDA8X17OxsUY5mzZpJN2/eFBudIyjt2rVrS7/++qt04cIFady4cZKfn5+qvIYYMGCANGbMGL3z9+7dk3x9faWYmBipsLBQql69urRnzx6tMFRuKhuVkfKbNWuWKHtsbKwqDbo+fPhw6cyZM+L3aNy4sShndHS0CPPuu+9KrVu3FnVM9bNr1y5p8+bN4trRo0dF2N27d4v7VO5j5MiR4r5GjBghynf69GkpKytLqlmzpjRw4EBx/Pfff0uhoaEirALt+/v7izzPnTsn2gil37dvX+mLL74Qv/HMmTMlDw8PKSEhQeteBw8eLI0aNcpoPTIMwzgSlpMsJ1lOMvaGFUnGKSEFjZQaUrZIOXF3d5eSkpKkNWvWSJ07dxZhIiIihFJAiqMhFKUkIyNDHEdFRUkuLi7SlStXxHFRUZFUq1YtoRQRpIgEBARIubm5Wuk0aNBAWrZsmUFFsk6dOkKJ04QUE0U5VRRJRdklSMGic4ryNWTIEOnpp5/WSmPYsGEqRdJQvgqUzrRp01THmZmZ4h63b99utG4pnc8//9xgnZOCpzB+/HhRDl1FkpREBVK+q1WrJi1ZskQc039SvHNyclRhli9frqVIkqL+2muvGSybUl9KWE2FkBRb+nigWd5KlSqJe1bYunWrUGxv3bqlikdlpt9aISwsTOrWrZvqmJRmamurV6/WynPixIlSz549DZaTYRjG0bCcZDmpCctJxh6waSvjlJAZaFZWlpgTSfMjyZSRzE179OghztE1Mmsl08r69euLONHR0cL8NSQkRJhdKmaRCQkJKjMQMj1dvXq1OI6IiBCmr4MHDxbHx48fF2aRZCLp5+en2uLj43Hp0iW9Mt6+fRuJiYkYPXq0Vvh///vfeuFbtmyp2g8ODhb/FbNb8qDaoUMHrfC6x6bQTNvX11fcu5K2IXJycoTZqSGz1uHDh6uOaZ9MctPS0ozmR+anZAKqeS90XTN93Xt55513sGbNGmH+OmnSJC1TZVOQuSk5AVKIjY0VJrp0zwpdunQRZsxUDoVmzZrB1VXdFZKJK6Wl4ObmJn5z3Tojc1nN+bgMwzDlCZaTLCd1YTnJ2Bp3m6fIMGVAw4YNxdy1vXv3ijl1pEASpLTQPLoDBw6IazQ/jiDFsk+fPmKjuZI0/44UyL59+2o5ZqG5eb/++ismT54s/tP1KlWqiGukgJCSpzk3U0GZr6gJhVfmNz722GNa10g50YQ8zmoqX5rxaWBROaegOzfRFJppK+kraRuC7lfXiczZs2dx5MgRoaR/9NFHqvNFRUVC8Sblz5z8zLmX/v374+rVq9i6dSt2796N3r17Cw+y33zzjcn71FQYjeWlWSZT5TWnzlJTU0U7YhiGKY+wnGQ5qQvLScbW8Igk49RfW0mpo00ZXSRIqdy5cycOHz6scrRz7tw54XTmyy+/FEuE0MijoVE5ciRDDlpo9HHdunVCsVRo27Ytbt26BXd3dyGgNTdF2dSERrZq1aolHPXohlecxpgDlfXo0aNa5zQ91hI0EkdKnS2gkVlSHHVHI7t37y4c+pBTHGWjEUO6Zsm9nDp1Cnl5eUbvhSAFjRzhkNI/f/58lcMeZcTRnHtt2rSpKCN9RFCgDww0+mgLL74xMTGirhiGYcorLCfVsJzUh+UkU1pYkWScWkDSchSkLCgjkgTt0yggLVOhKJJk4kpCZMGCBUKxI8+lM2fO1EuTFLzOnTsLc1Ty3EmmsApPPPEEOnXqJLx8kqJKHlfJ7HLatGkGlSFl3SryJPrf//5XrGVJSip5ICWvq+YyduxYbNu2TcS5cOECli1bhu3bt2uNqpG3VDKxpboghVlTUbMUGoUlr7GKslZQUID//e9/ePnll9G8eXOt7Y033hBKd0meazUVdRrZI++pZHpK9aiMNCr38+mnn+KPP/7AxYsXcebMGWzZskV4vSXIfJlMSnfs2IGkpCThRdcY9BGATGhHjhwplD4aoaa6JI+zpOSXBjJppfumEW6GYZjyCstJlpMsJxl7wook49QCkubz0QifpmJAimRGRoZYCoSWzFBGuGhJjLVr14ovcDQyacxUkhQQUowGDhwolBYFUnRIoaOROVregka1hg4dKhRKY4oJKVrff/+9yJvmJlDZaN+SEUma10fLkpAiSXP+SImaOHGi1jzDF198Ef369RN1QveqzPO0hqeeekqYdpJZKUFK9507d8QSIrrQ0hx0X+aOStKSKX/++adQeGkO5NSpU4XiSCj3Qwr/xx9/LOZSUl2TGTDNmSRoNPjbb78VyjQt86Gp6OtCy52QokomqO3bt8egQYOEmezChQtRWkjRpY8TNLrNMAxTXmE5yXKS5SRjT1zI445dc2AYxua8+eabwlyXHA3ZA1rrkpQlUsTszapVq8TCxfTVVFNxL8+Qg6AJEyaIEVaGYRim/MFy0rGwnHw4YGc7DOME0Ojpk08+KSbKk1nrypUrhbJnL8j0lBzu0MgueXm1JT///LPwpEvzR2nkl5z3kGdcZ1EiaW4tjW6SqS/DMAxTPmA5WX5gOfnwwCOSDOMEkKJFToVIsSMljOb6jRkzBs7I7NmzhRJMjovICy7NOf3iiy+EKSrDMAzDWAPLSYYpe1iRZBiGYRiGYRiGYSyCne0wDMMwDMMwDMMwFsGKJMMwDMMwDMMwDGMRrEgyDMMwDMMwDMMwFsGKJMMwDMMwDMMwDGMRrEgyDMMwDMMwDMMwFsGKJMMwDMMwDMMwDGMRrEgyDMMwDMMwDMMwFsGKJMMwDMMwDMMwDANL+H/jSNn8BSbkXwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#the new sherpa ids for the cleaned heg-1, heg+1, meg-1 and meg+1 spectra\n",
    "spec_ids_clean = [15,16,21,22]\n",
    "\n",
    "#set the analysis space to wavelength so it plots in Angstroms.\n",
    "for i in spec_ids_clean:\n",
    "    set_analysis(i,'wave')\n",
    "\n",
    "#bin num was set in earlier cell and should be the same here\n",
    "for i in spec_ids_clean:\n",
    "    group_width(i, bin_num)\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "\n",
    "#plot the original (confused) spectra in red\n",
    "plot(\"data\", 3, \"data\", 4, \"data\", 9, \"data\", 10, \n",
    "     color='red',\n",
    "     label=['confused','confused','confused','confused'], \n",
    "     yerrorbars=False, linestyle='-', marker=None)\n",
    "\n",
    "#overplot the new 'cleaned' spectra in blue\n",
    "plot(\"data\", 15, \"data\", 16, \"data\", 21, \"data\", 22, \n",
    "     color='blue',\n",
    "     label=['cleaned','cleaned','cleaned','cleaned'],\n",
    "     overplot=True, yerrorbars=False, linestyle='-', marker=None)\n",
    "\n",
    "# set the same x-limits for all panels:\n",
    "axes = plt.gcf().axes\n",
    "for ax, arm in zip(axes,arm_label):\n",
    "    ax.set_xlim(0,20)\n",
    "    ax.set_title(arm)\n",
    "    ax.legend()\n",
    "\n",
    "#label the figure with color\n",
    "fig = plt.gcf()\n",
    "fig.text(0.30, 0.95, \"Confused\",  ha='left',  va='center', color='red',  fontsize=16)\n",
    "fig.text(0.425, .95, \"vs\",    va='center', color='black',  fontsize=16)\n",
    "fig.text(0.565, .95, \"Cleaned\", ha='right', va='center', color='blue', fontsize=16)\n",
    "plt.draw()\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce061207",
   "metadata": {},
   "source": [
    "In the confused regions the flux (blue) is set to zero compared to the red spectra while in the other regions the blue and red spectra are identical (and the blue line is plotted on top of the red line). A similar comparison can be made between the original (confused) and cleaned arfs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "72da9d9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 5))\n",
    "#original ARFs\n",
    "plot(\"arf\", 3, \"arf\", 4, \"arf\", 9, \"arf\", 10,\n",
    "     label=['confused','confused','confused','confused'],\n",
    "     color='red')\n",
    "#cleaned ARFs\n",
    "plot(\"arf\", 15, \"arf\", 16, \"arf\", 21, \"arf\", 22, \n",
    "     label=['cleaned','cleaned','cleaned','cleaned'], \n",
    "     color='blue', overplot=True)\n",
    "\n",
    "axes = plt.gcf().axes\n",
    "for ax, arm in zip(axes,arm_label_arf):\n",
    "    ax.set_xlim(0, 20)\n",
    "    ax.set_title(arm)\n",
    "\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7518031a",
   "metadata": {},
   "source": [
    "The plot shows that several portions of each spectrum have been identified to have events associated with other sources in the field assigned to the extracted COUP 394 source (i.e., confusion). What looked like an emission line at 8.5 Å in the meg+1 spectrum turns out to be emission from a different source crossing the extracted spectrum. The narrow ranges of confusion are typically associated with point sources or spectral intersection whereas the large bandpasses of confusion are typically the result of arm confusion (e.g., another bright source falling on the dispersed arm of the extract source.)\n",
    "\n",
    "The confusion tables list specific instances of confusion and the source causing them. The code below lists confusion the MEG arm data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "777082fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " \n",
       "--------------------------------------------------------------------------------\n",
       "Data for Table Block TABLE\n",
       "--------------------------------------------------------------------------------\n",
       " \n",
       "ROW    confuser_srcid grating_type order      confusion_type confusion_wave       wave_low             wave_high            flag\n",
       " \n",
       "     1        696 meg            1 spec           2.6126691536         1.9454580533         3.2798802538 confused  \n",
       "     2       1390 meg            1 spec           8.9880208912         8.3208097909         9.6552319914 confused  \n",
       "     3        187 meg            1 pnt            8.9045904665         8.7486201313         9.0605608017 confused  \n",
       "     4        515 meg           -1 pnt            2.6398747791         2.6172583374         2.6624912208 confused  \n",
       "     5        652 meg           -1 pnt            4.6294335817         4.6025095872         4.6563575761 confused  \n",
       "     6       1113 meg           -1 pnt           11.2665089081        11.1864092180        11.3466085981 confused  \n",
       "     7        187 meg           -1 arm            4.4522952332                3.970                5.180 confused  \n",
       "     8        187 meg           -1 arm            8.9045904665                7.290               12.750 confused  \n",
       "     9        187 meg            1 arm            2.2261476166                2.140                2.330 confused  \n",
       "    10        187 meg            1 arm            2.9681968222                2.840                3.120 confused  \n",
       "    11        187 meg            1 arm            4.4522952332                4.270                4.660 confused  \n",
       "    12        652 meg           -1 arm                     1.0               21.840               31.990 confused  \n",
       "    13        652 meg           -1 arm            2.3147167908                2.250                2.390 confused  \n",
       "    14        652 meg           -1 arm            1.5431445272                 1.50                1.590 confused  \n",
       "    15        652 meg            1 arm                     1.0               21.840               31.990 confused  \n",
       "    16        652 meg            1 arm            4.6294335817                3.980                5.770 confused  \n",
       "    17        652 meg            1 arm            2.3147167908                2.130                2.560 confused  \n",
       "    18       1113 meg           -1 arm            5.6332544540                5.380                5.930 confused  \n",
       "    19       1113 meg           -1 arm            3.7555029694                3.570                3.970 confused  \n",
       "    20       1113 meg           -1 arm            2.8166272270                2.690                2.970 confused  \n",
       "    21       1113 meg            1 arm            5.6332544540                4.960                 6.70 confused"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dmlist.punlearn\n",
    "dmlist.infile = f'{cc_table_coup}[cols confuser_srcid, grating_type, order, confusion_type, confusion_wave, wave_low, wave_high, flag][flag=confused, order=-1,+1, grating_type=meg]'\n",
    "dmlist.opt='data'\n",
    "dmlist.rows=30\n",
    "\n",
    "dmlist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a59afa6",
   "metadata": {},
   "source": [
    "From the table, it appears that the MEG+1 wavelength range of ~8-9.5 Å is affected by two sources of confusion. A 0th order point source (COUP 187) landed right on the dispersed spectrum and the dispersed spectrum of COUP 1390 also intersected with the extracted MEG+1 spectrum."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36ccf94c",
   "metadata": {},
   "source": [
    "The events assigned to the HEG or MEG spectrum can be visually assessed to see how well crisscross identified confusion. This plotting method only works on evt2 files made for the extracted source of interest which in this case is COUP 394 since the grating coordiantes in the evt2 files are relative to that (a listing of the column names in the evt2 file is below). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a7ff2e80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['time',\n",
       " 'expno',\n",
       " 'rd(tg_r, tg_d)',\n",
       " 'chip(chipx, chipy)',\n",
       " 'tdet(tdetx, tdety)',\n",
       " 'det(detx, dety)',\n",
       " 'sky(x, y)',\n",
       " 'ccd_id',\n",
       " 'pha',\n",
       " 'pi',\n",
       " 'energy',\n",
       " 'grade',\n",
       " 'fltgrade',\n",
       " 'node_id',\n",
       " 'tg_m',\n",
       " 'tg_lam',\n",
       " 'tg_mlam',\n",
       " 'tg_srcid',\n",
       " 'tg_part',\n",
       " 'tg_smap',\n",
       " 'status']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use pycrates to read in the event file and inspect the columns.\n",
    "from pycrates import read_file\n",
    "\n",
    "evt2_file = f'{obsid}/repro/{src_root}_repro_evt2.fits'\n",
    "evt_data = read_file(evt2_file)\n",
    "evt_data.get_colnames()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dae4db6a",
   "metadata": {},
   "source": [
    "The relevant HETG event values are copied to new arrays for plotting. HETG event files contain extra columns for events associated with the extracted spectrum compared to ACIS imaging observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4e0f5157",
   "metadata": {},
   "outputs": [],
   "source": [
    "# HETG wavelength assigned to each event\n",
    "tg_lam = evt_data.tg_lam.values\n",
    "# cross-dispersion distance (distance from 0th order) of each event\n",
    "tg_d = evt_data.rd.tg_d.values\n",
    "# dispersion order (e.g., +1,-1) assigned to each event\n",
    "tg_m = evt_data.tg_m.values\n",
    "# order multiplied with the wavelength for each event\n",
    "tg_mlam = evt_data.tg_mlam.values\n",
    "#  ACIS CCD-derived energy of the event\n",
    "energy = evt_data.energy.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "acfeca7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_evt_crate(evt_crate, order_val, arm_par, tgd_par):\n",
    "    \"\"\"\n",
    "    Function for filtering a crate evt file to return the event rows that satisfy \n",
    "    the HETG order, arm type (meg/heg) and tg_d value conditions. \n",
    "    \"\"\"\n",
    "    crate_elements = (evt_crate.tg_m.values == order_val) & \\\n",
    "                     (evt_crate.tg_part.values == arm_par) & \\\n",
    "                     (np.abs(evt_crate.rd.tg_d.values) < tgd_par)\n",
    "\n",
    "    return(crate_elements)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54e62664",
   "metadata": {},
   "source": [
    "This function filters the event file to retrieve order- and arm-specific event information for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6a91558e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create the filters for plotting only the relevant orders and arm type\n",
    "meg_p1 = filter_evt_crate(evt_data, 1, 2, 8E-3)\n",
    "meg_m1 = filter_evt_crate(evt_data,-1, 2, 8E-3)\n",
    "heg_p1 = filter_evt_crate(evt_data, 1, 1, 8E-3)\n",
    "heg_m1 = filter_evt_crate(evt_data, -1, 1, 8E-3)\n",
    "\n",
    "fig, ax = plt.subplots(\n",
    "    nrows=1, ncols=2,                # 2 rows, 2 columns\n",
    "    figsize=(16, 5),                # optional: figure size in inches\n",
    ")\n",
    "\n",
    "# MEG PLOT\n",
    "ax[0].scatter(-1*tg_lam[meg_m1], tg_d[meg_m1], s=1, color='green')\n",
    "ax[0].scatter(tg_lam[meg_p1], tg_d[meg_p1], s=1, color='blue')\n",
    "ax[0].plot([-30,30], [6.4E-4, 6.4E-4], color='orange') #default extraction width for HETG spectra\n",
    "ax[0].plot([-30,30], [-6.4E-4, -6.4E-4], color='orange')\n",
    "ax[0].set_title('MEG -1 and +1')\n",
    "\n",
    "# HEG PLOT\n",
    "ax[1].scatter(-1*tg_lam[heg_m1], tg_d[heg_m1], s=1, color='green')\n",
    "ax[1].scatter(tg_lam[heg_p1], tg_d[heg_p1], s=1, color='blue')\n",
    "ax[1].set_title('HEG -1 and +1')\n",
    "ax[1].plot([-15,15], [6.4E-4, 6.4E-4], color='orange')\n",
    "ax[1].plot([-15,15], [-6.4E-4, -6.4E-4], color='orange')\n",
    "\n",
    "for i in ax:\n",
    "    i.set_xlabel('m * Wavelength [Angstrom]')\n",
    "    i.set_ylabel('Cross Dispersion Angle [deg]')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dd6154f",
   "metadata": {},
   "source": [
    "The above plot shows the MEG (left) and HEG (right) events associated with the CIAO extraction of COUP 394 source. Specifically, the events within the orange box will be those that are included in the PHA2 spectrum. The X-axis denotes the order * wavelength, so photons seen in a negative dispersion order are plotted at negative numbers.\n",
    "The y-axis denotes the cross dispersion angle (tg_d) in degrees, essentially the distance between a count and the middle of the line of dispersed photons.\n",
    "\n",
    "A single unconfused source should only show events within the orange box. The MEG+1 plot (right, blue) shows a strong vertical line at about 9 Å which is the location of a 0th order (point source) field star that happened to fall on the dispersed spectrum of the extracted source. The vertical nature of this feature is due to the size of the PSF of that source. Many of those 0th-order events match the appropriate energy (e.g., 9 Å) to erroneously be assigned to the MEG+1 spectrum of COUP 394. Other fainter 0th-order confusing sources can be seen in MEG-1 at approximately -11 and -5 Å. The two large horizontal features shown in the MEG plot at y\\~0.008 and -0.006 represent the dispersed spectra of other stars in the field which are close to the extracted source. However, only events with a small range in cross dispersion angle (\\~+/- 6.3E-4) and assigned to the extracted source with CIAO tools.\n",
    "\n",
    "The HEG -1 plot shows many examples of spectral-intersection confusion (e.g., the dispersed arm of another source overlapping the extracted source at the wavelength expected by ACIS order sorting). These are seens as with slanted lines at approximately -6.5 and -9 Å. \n",
    "\n",
    "These plots can be hard to read when many sources are present, so the next plot filters out only the events within the orragne regions. For those events, the energy detected by the ACIS CCDs is then shown on the y-axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d85e18be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# REDO the filtering with a smaller tg_d window to remove events outside default HETG extraction window\n",
    "meg_p1 = filter_evt_crate(evt_data, 1, 2, 4.6E-4)\n",
    "meg_m1 = filter_evt_crate(evt_data,-1, 2, 4.6E-4)\n",
    "heg_p1 = filter_evt_crate(evt_data, 1, 1, 4.6E-4)\n",
    "heg_m1 = filter_evt_crate(evt_data, -1, 1, 4.6E-4)\n",
    "\n",
    "# Display all events assigned to orders -3,-2,-1,+1,+2,+3\n",
    "all_evts_meg_filt = (np.abs(evt_data.tg_m.values) <= 3) & (evt_data.tg_part.values == 2)\n",
    "all_evts_heg_filt = (np.abs(evt_data.tg_m.values) <= 3 ) & (evt_data.tg_part.values == 1)\n",
    "\n",
    "\n",
    "# Create a 2×2 figure (4 sub‑plots)\n",
    "fig, ax = plt.subplots(\n",
    "    nrows=1, ncols=2,                # 2 rows, 2 columns\n",
    "    figsize=(16, 5),                # optional: figure size in inches\n",
    ")\n",
    "\n",
    "ax[0].scatter(tg_mlam[all_evts_meg_filt], energy[all_evts_meg_filt], s=1, color='grey')\n",
    "ax[0].scatter(tg_mlam[meg_m1], energy[meg_m1], s=1, color='green')\n",
    "ax[0].scatter(tg_mlam[meg_p1], energy[meg_p1], s=1, color='blue')\n",
    "ax[0].set_title('MEG -1 and +1')\n",
    "\n",
    "\n",
    "ax[1].scatter(tg_mlam[all_evts_heg_filt], energy[all_evts_heg_filt], s=1, color='grey')\n",
    "ax[1].scatter(tg_mlam[heg_m1], energy[heg_m1], s=1, color='green')\n",
    "ax[1].scatter(tg_mlam[heg_p1], energy[heg_p1], s=1, color='blue')\n",
    "ax[1].set_title('HEG -1 and +1')\n",
    "\n",
    "for i in ax:\n",
    "    i.set_ylim(300,7500)\n",
    "    i.set_xlabel('m * Wavelength [Angstrom]')\n",
    "    i.set_ylabel('ACIS Energy [eV]')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50c0ec9f",
   "metadata": {},
   "source": [
    "The above plots are the so-called HETG 'banana plots' and help reveal the extent to which a source's arm/order suffers from confusion. The HETG gratings equation determines the wavelength of every event based on its position along the dispersion direction from the 0th order. This wavelength (energy) is then compared to the ACIS CCD-determined energy of the same source to ensure it is compatible with the gratings-derived energy (wavelength). Only events whose ACIS CCD energy is consistent with the gratings-determined energy are ultimately assigned to the extracted spectrum with standard CIAO tools. Shown here in gray are all events assigned to any of the -3, -2, -1, +1, +2, +3 orders. The green and blue events are -1/+1 events that fall within the 4.6E-4 cross dispersion direction denoted by the yellow bars in the previous plots. \n",
    "\n",
    "Looking closer at the MEG+1 portion of the spectrum one can see the previously discussed 'point source confusion' at \\~9 Å. It shows us as a vertical bar in all three positive orders because the 0th order contains events at all energies and not just at 9 Å. Also note the curved feature starting at \\~13 Å in the MEG+3 order (grey) and bending ultimately towards the MEG+1 order at \\~ 20 Å. This is a clear indication of arm confusion from a source somewhere else on the detector but in line with the dispersed spectrum of our extracted source. The confusing source would likely contaminate all portions of the MEG+1 spectrum >\\~ 20 Å."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eb9954a",
   "metadata": {},
   "source": [
    "`crisscross` and its helper tool `clean_spec` facilitate the analysis of spectra from crowded HETG fields. The next and final step would be to fit the spectra with a model and learn something about the underlying astrophysics. This is beyond the scope of this tutorial but there are other CIAO tools that help with this process."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67dca0e9",
   "metadata": {},
   "source": [
    "## (2) Run crisscross for a single source on multiple ObsIDs and combine the spectra"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8c3d3eb",
   "metadata": {},
   "source": [
    "Most HETG observations are campaigns with multiple ObsIDs. crisscross can process multiple observations and generate confusion tables for multiple sources in each ObsID. Users should see the `crisscross` and `clean_spec` help files for more examples of how this is done. The following example explains how to assess confusion for a single source over multiple ObsIDs. \n",
    "\n",
    "First, download two more Orion Nebula Cluster pre-main sequence star observations and re-process them so `chandra_repro` extracts spectra of COUP 394."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "edf244e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[True, True]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# NOTE -- download_chandra_obsid will only download ObsIDs that are not on disk yet, is it doesn't hurt or list it again.\n",
    "obsid_list = [3, 22999, 23000]\n",
    "download_chandra_obsids(obsid_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "94052d38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters for chandra_repro:\n",
      "\n",
      "Required parameters:\n",
      "               indir = 22999            Input directory\n",
      "              outdir =                  Output directory (default = $indir/repro)\n",
      "\n",
      "Optional parameters:\n",
      "                root = COUP_394         Root for output filenames\n",
      "            badpixel = True             Create a new bad pixel file?\n",
      "      process_events = True             Create a new level=2 event file?\n",
      "            destreak = True             Destreak the ACIS-8 chip?\n",
      "          set_ardlib = True             Set ardlib.par with the bad pixel file?\n",
      "        check_vf_pha = False            Clean ACIS background in VFAINT data?\n",
      "             pix_adj = default          Pixel randomization: default|edser|none|randomize\n",
      "      tg_zo_position = 83.79475306,-5.39575306  Method to determine gratings 0th order location: evt2|detect|R.A. & Dec.\n",
      "           tg_orders = default          List of orders to extract: none, default, or comma separated list\n",
      "         asol_update = True             If necessary, apply boresight correction to aspect solution file?\n",
      "           pi_filter = True             Apply PI background filter to HRC-S+LETG data?\n",
      "       patch_hrc_ssc = False            Patch HRC Secondary Science Corruption?\n",
      "             cleanup = True             Cleanup intermediate files on exit\n",
      "             clobber = False            Clobber existing file\n",
      "             verbose = 1                Debug Level(0-5)\n",
      "Parameters for chandra_repro:\n",
      "\n",
      "Required parameters:\n",
      "               indir = 23000            Input directory\n",
      "              outdir =                  Output directory (default = $indir/repro)\n",
      "\n",
      "Optional parameters:\n",
      "                root = COUP_394         Root for output filenames\n",
      "            badpixel = True             Create a new bad pixel file?\n",
      "      process_events = True             Create a new level=2 event file?\n",
      "            destreak = True             Destreak the ACIS-8 chip?\n",
      "          set_ardlib = True             Set ardlib.par with the bad pixel file?\n",
      "        check_vf_pha = False            Clean ACIS background in VFAINT data?\n",
      "             pix_adj = default          Pixel randomization: default|edser|none|randomize\n",
      "      tg_zo_position = 83.79475306,-5.39575306  Method to determine gratings 0th order location: evt2|detect|R.A. & Dec.\n",
      "           tg_orders = default          List of orders to extract: none, default, or comma separated list\n",
      "         asol_update = True             If necessary, apply boresight correction to aspect solution file?\n",
      "           pi_filter = True             Apply PI background filter to HRC-S+LETG data?\n",
      "       patch_hrc_ssc = False            Patch HRC Secondary Science Corruption?\n",
      "             cleanup = True             Cleanup intermediate files on exit\n",
      "             clobber = False            Clobber existing file\n",
      "             verbose = 1                Debug Level(0-5)\n"
     ]
    }
   ],
   "source": [
    "# Run chandra repro using the zeroth order source location for COUP 394\n",
    "# Note: ObsID 3 was reprocessed above, so no need to do it again.\n",
    "\n",
    "for i in [22999, 23000]:\n",
    "    chandra_repro.punlearn()\n",
    "    chandra_repro.indir = i\n",
    "    chandra_repro.root = src_root\n",
    "    chandra_repro.tg_zo_position = f'{src_RA},{src_DEC}'\n",
    "    chandra_repro.clobber=False\n",
    "\n",
    "    print(chandra_repro)\n",
    "\n",
    "    a = chandra_repro()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6a5d798",
   "metadata": {},
   "source": [
    "Instead of running crisscross with a single evt2 file, here we will use a list of the three ObsIDs. They are identified with glob."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "52a0a657",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['22999/repro/COUP_394_repro_evt2.fits', '3/repro/COUP_394_repro_evt2.fits', '23000/repro/COUP_394_repro_evt2.fits']\n"
     ]
    }
   ],
   "source": [
    "#create a list of evt2 files\n",
    "evt2_list = glob.glob(f'*/repro/{src_root}_repro_evt2.fits')\n",
    "print(evt2_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "233d7e98",
   "metadata": {},
   "source": [
    "Crisscross output is saved to to a new directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f5c4a5e7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "crisscross\n",
       "          infile = 22999/repro/COUP_394_repro_evt2.fits,3/repro/COUP_394_repro_evt2.fits,23000/repro/COUP_394_repro_evt2.fits\n",
       "          outdir = cc_tutorial_multiobs\n",
       "       main_list = full_coup_src_list.tsv\n",
       " subset_src_list = \n",
       "  single_src_pos = 83.79475306,-5.39575306\n",
       " single_src_root = COUP_394\n",
       "  wavdetect_file = None\n",
       "conf_table_level = confused\n",
       "  arf_ratios_dir = $ASCDS_CALIB\n",
       " max_pntsrc_dist = 8\n",
       "min_pntsrc_counts = 5\n",
       " min_spec_counts = 3\n",
       "min_spec_confuser_counts = 50\n",
       "       osip_frac = 1\n",
       "spec_confuse_limit = 0.1\n",
       "    max_arm_dist = 8\n",
       "  min_arm_counts = 50\n",
       "        arm_nsig = 6\n",
       "arm_confuse_limit = 0.1\n",
       "  meg_cutoff_low = 1\n",
       " meg_cutoff_high = 32\n",
       "  heg_cutoff_low = 1\n",
       " heg_cutoff_high = 16\n",
       "   highest_order = 3\n",
       "        min_tg_d = -0.00066\n",
       "        max_tg_d = 0.00066\n",
       "         verbose = 1\n",
       "         clobber = yes\n",
       "            mode = hl\n",
       "\n",
       "\n",
       "\n",
       "CrissCross Time Start:\n",
       "Thu Jun 18 12:08:45 2026\n",
       "\n",
       "\n",
       "This run is for observation \"22999/repro/COUP_394_repro_evt2.fits\".\n",
       "\n",
       "No input wavdetect source fits table provided so running wavdetect on 22999/repro/COUP_394_repro_evt2.fits with binsize=2.0, bands=broad and psfecf=0.9.\n",
       "If you wish to use other wavdetect parameters please run wavdetect and provide a wavdetect source fits table with parameter 'wavdetect_file'.\n",
       "\n",
       "The total number of X-ray field sources input is 1616. These will be assessed as potential sources of confusion for sources in 'subset_src_list' or 'single_src_pos'.\n",
       "\n",
       "total elapsed time has been 0.92 minutes.\n",
       "\n",
       "\n",
       "\n",
       "CrissCross Time Start:\n",
       "Thu Jun 18 13:16:19 2026\n",
       "\n",
       "\n",
       "This run is for observation \"3/repro/COUP_394_repro_evt2.fits\".\n",
       "\n",
       "No input wavdetect source fits table provided so running wavdetect on 3/repro/COUP_394_repro_evt2.fits with binsize=2.0, bands=broad and psfecf=0.9.\n",
       "If you wish to use other wavdetect parameters please run wavdetect and provide a wavdetect source fits table with parameter 'wavdetect_file'.\n",
       "\n",
       "The total number of X-ray field sources input is 1616. These will be assessed as potential sources of confusion for sources in 'subset_src_list' or 'single_src_pos'.\n",
       "\n",
       "total elapsed time has been 1.06 minutes.\n",
       "\n",
       "\n",
       "\n",
       "CrissCross Time Start:\n",
       "Thu Jun 18 13:17:22 2026\n",
       "\n",
       "\n",
       "This run is for observation \"23000/repro/COUP_394_repro_evt2.fits\".\n",
       "\n",
       "No input wavdetect source fits table provided so running wavdetect on 23000/repro/COUP_394_repro_evt2.fits with binsize=2.0, bands=broad and psfecf=0.9.\n",
       "If you wish to use other wavdetect parameters please run wavdetect and provide a wavdetect source fits table with parameter 'wavdetect_file'.\n",
       "\n",
       "The total number of X-ray field sources input is 1616. These will be assessed as potential sources of confusion for sources in 'subset_src_list' or 'single_src_pos'.\n",
       "\n",
       "total elapsed time has been 0.85 minutes."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crisscross(infile=evt2_list, outdir='cc_tutorial_multiobs',\n",
    "           main_list='full_coup_src_list.tsv',\n",
    "           single_src_pos=f'{src_RA},{src_DEC}', \n",
    "           single_src_root=src_root, clobber=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2577d716",
   "metadata": {},
   "source": [
    "To run `clean_spec` on multiple pha2 files the user needs to provide a list of pha2_files and the relevant crisscross confusion table files. Cleaned spectra are saved to a new directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3613d762",
   "metadata": {},
   "outputs": [],
   "source": [
    "pha2_list = sorted(glob.glob(f'*/repro/{src_root}_repro_pha2.fits'))\n",
    "cc_table_list = sorted(glob.glob(f'cc_tutorial_multiobs/*/*/table_fits_data/*.fits'))\n",
    "\n",
    "spec_dir = 'coup394_multiobs_spec'\n",
    "os.makedirs(spec_dir, exist_ok=True)\n",
    "\n",
    "for pha2, cc_table in zip(pha2_list, cc_table_list):\n",
    "    clean_spec(infile=pha2,\n",
    "               conf_file=cc_table,\n",
    "               spec_root=f'{spec_dir}/{src_root}', \n",
    "               arf_file=None, resp_dir=None, clobber=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edf719db",
   "metadata": {},
   "source": [
    "Now there is a set of cleaned spectra from three ObsIDs, which will be combined with the CIAO tool `combine_grating_spectra`. This can be used for visualization purposes because it can combine multiple spectra of the same source from different obsIDs. It can also combine the +1 and -1 orders of the same arm. It should be noted that it is typically not best practice to fit combined spectra. Instead, users are encouraged to perform joint-fits on the individual spectra and use combined spectra for visualization purposes only. Moreover, caution should be taken when combining spectra from sources that undergo significant variability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7251e551",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters for combine_grating_spectra:\n",
      "\n",
      "Required parameters:\n",
      "              infile = */repro/COUP_394*_pha2.fits  Source PHA1/PHA2 grating spectra to combine; enter list or '@stack'\n",
      "             outroot = combined_spec/COUP_394_original  Root name for output file(s)\n",
      "\n",
      "Optional parameters:\n",
      "       add_plusminus = True             Combine +/- orders (yes) after summing signed-order and part?\n",
      "                garm = all              Grating arm (HEG, MEG, LEG, or 'all')\n",
      "               order = 1                Grating diffraction order (1,2,3,-1,-2,-3, or 'all')\n",
      "                 arf = */repro/tg/*.arf  Source ARF files to combine; enter list or '@stack'\n",
      "                 rmf = */repro/tg/*.rmf  Source RMF files to combine; enter list or '@stack'\n",
      "             bkg_pha =                  Background PHA files to combine; enter list or '@stack'\n",
      "       bscale_method = counts           How are BACKSCAL and background counts computed?\n",
      "       exposure_mode = sum              Sum or average exposure times?\n",
      "              object =                  Specify the OBJECT keyword in the combined output\n",
      "             clobber = False            OK to overwrite existing output file?\n",
      "             verbose = 1                Debug Level(0-5)\n"
     ]
    }
   ],
   "source": [
    "#make a directory to hold the combine_grating_spectra combined files.\n",
    "comb_spec = 'combined_spec'\n",
    "os.makedirs(comb_spec, exist_ok=True)\n",
    "\n",
    "#combine the original 'confused' spectra\n",
    "combine_grating_spectra.punlearn()\n",
    "combine_grating_spectra.infile=f'*/repro/{src_root}*_pha2.fits'\n",
    "combine_grating_spectra.arf=f'*/repro/tg/*.arf'\n",
    "combine_grating_spectra.rmf=f'*/repro/tg/*.rmf'\n",
    "combine_grating_spectra.outroot=f'{comb_spec}/{src_root}_original'\n",
    "combine_grating_spectra.add_plusminus='yes'\n",
    "combine_grating_spectra.order=1\n",
    "combine_grating_spectra.clobber=False\n",
    "\n",
    "print(combine_grating_spectra)\n",
    "\n",
    "a = combine_grating_spectra()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48d4f74f",
   "metadata": {},
   "source": [
    "`combine_grating_spectra` looks for rmfs in the same directory structure as the PHA2 files so the original RMFs have to be copied to the new 'cleaned' directory to combine all the cleaned files and responses. This is usually managable but RMFs can be relatively large files, so soft links or other ways to minimize disk usage might be useful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0c3819b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['22999/repro/tg/COUP_394_repro_heg_m1.rmf', '22999/repro/tg/COUP_394_repro_heg_p1.rmf', '22999/repro/tg/COUP_394_repro_meg_m1.rmf', '22999/repro/tg/COUP_394_repro_meg_p1.rmf', '23000/repro/tg/COUP_394_repro_heg_m1.rmf', '23000/repro/tg/COUP_394_repro_heg_p1.rmf', '23000/repro/tg/COUP_394_repro_meg_m1.rmf', '23000/repro/tg/COUP_394_repro_meg_p1.rmf', '3/repro/tg/COUP_394_repro_heg_m1.rmf', '3/repro/tg/COUP_394_repro_heg_p1.rmf', '3/repro/tg/COUP_394_repro_meg_m1.rmf', '3/repro/tg/COUP_394_repro_meg_p1.rmf']\n"
     ]
    }
   ],
   "source": [
    "#ID the original RMFs and make a copy in the spec_dir\n",
    "rmf_list = sorted(glob.glob(f'*/repro/tg/*.rmf'))\n",
    "print(rmf_list)\n",
    "\n",
    "for i in rmf_list:\n",
    "    shutil.copy2(i, spec_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fc641036",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters for combine_grating_spectra:\n",
      "\n",
      "Required parameters:\n",
      "              infile = coup394_multiobs_spec/*.pha2  Source PHA1/PHA2 grating spectra to combine; enter list or '@stack'\n",
      "             outroot = combined_spec/COUP_394_cleaned  Root name for output file(s)\n",
      "\n",
      "Optional parameters:\n",
      "       add_plusminus = True             Combine +/- orders (yes) after summing signed-order and part?\n",
      "                garm = all              Grating arm (HEG, MEG, LEG, or 'all')\n",
      "               order = 1                Grating diffraction order (1,2,3,-1,-2,-3, or 'all')\n",
      "                 arf = coup394_multiobs_spec/*.arf  Source ARF files to combine; enter list or '@stack'\n",
      "                 rmf = coup394_multiobs_spec/*.rmf  Source RMF files to combine; enter list or '@stack'\n",
      "             bkg_pha =                  Background PHA files to combine; enter list or '@stack'\n",
      "       bscale_method = counts           How are BACKSCAL and background counts computed?\n",
      "       exposure_mode = sum              Sum or average exposure times?\n",
      "              object =                  Specify the OBJECT keyword in the combined output\n",
      "             clobber = False            OK to overwrite existing output file?\n",
      "             verbose = 1                Debug Level(0-5)\n"
     ]
    }
   ],
   "source": [
    "#combine the cleaned spectra\n",
    "combine_grating_spectra.punlearn()\n",
    "combine_grating_spectra.infile=f'{spec_dir}/*.pha2'\n",
    "combine_grating_spectra.arf=f'{spec_dir}/*.arf'\n",
    "combine_grating_spectra.rmf=f'{spec_dir}/*.rmf'\n",
    "combine_grating_spectra.outroot=f'{comb_spec}/{src_root}_cleaned'\n",
    "combine_grating_spectra.add_plusminus='yes'\n",
    "combine_grating_spectra.order=1\n",
    "combine_grating_spectra.clobber=False\n",
    "\n",
    "print(combine_grating_spectra)\n",
    "\n",
    "a = combine_grating_spectra()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d88efb9b",
   "metadata": {},
   "source": [
    "The code below loads the COUP 394 spectra combined from three ObsIDs into sherpa and plots the comparison of the confused vs cleaned spectra again. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b5860589",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read ARF file combined_spec/COUP_394_original_combo_heg_abs1.arf\n",
      "read RMF file combined_spec/COUP_394_original_combo_heg_abs1.rmf\n",
      "read background file combined_spec/COUP_394_original_combo_heg_abs1_bkg.pha\n",
      "read ARF file combined_spec/COUP_394_original_combo_meg_abs1.arf\n",
      "read RMF file combined_spec/COUP_394_original_combo_meg_abs1.rmf\n",
      "read background file combined_spec/COUP_394_original_combo_meg_abs1_bkg.pha\n",
      "read ARF file combined_spec/COUP_394_cleaned_combo_heg_abs1.arf\n",
      "read RMF file combined_spec/COUP_394_cleaned_combo_heg_abs1.rmf\n",
      "read background file combined_spec/COUP_394_cleaned_combo_heg_abs1_bkg.pha\n",
      "read ARF file combined_spec/COUP_394_cleaned_combo_meg_abs1.arf\n",
      "read RMF file combined_spec/COUP_394_cleaned_combo_meg_abs1.rmf\n",
      "read background file combined_spec/COUP_394_cleaned_combo_meg_abs1_bkg.pha\n"
     ]
    }
   ],
   "source": [
    "orig_heg = f'{comb_spec}/COUP_394_original_combo_heg_abs1.pha'\n",
    "orig_meg = f'{comb_spec}/COUP_394_original_combo_meg_abs1.pha'\n",
    "cleaned_heg = f'{comb_spec}/COUP_394_cleaned_combo_heg_abs1.pha'\n",
    "cleaned_meg = f'{comb_spec}/COUP_394_cleaned_combo_meg_abs1.pha'\n",
    "\n",
    "#run clean so we can override the previous example's sherpa environment\n",
    "clean()\n",
    "load_data(1,orig_heg, use_errors=True)\n",
    "load_data(2,orig_meg, use_errors=True)\n",
    "load_data(3,cleaned_heg, use_errors=True)\n",
    "load_data(4,cleaned_meg, use_errors=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "19194049",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataset 1: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 2: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 3: 1:21.48 Wavelength (Angstrom)\n",
      "dataset 4: 1:41.96 Wavelength (Angstrom)\n",
      "dataset 1: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 2: 1:41.96 Wavelength (Angstrom) (unchanged)\n",
      "dataset 3: 1:21.48 Wavelength (Angstrom) (unchanged)\n",
      "dataset 4: 1:41.96 Wavelength (Angstrom) (unchanged)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#the sherpa ids of the combined datasets\n",
    "combined_specs = [1,2,3,4]\n",
    "\n",
    "#set the analysis to wavelength so we can plot in Angstrom\n",
    "for i in combined_specs:\n",
    "    set_analysis(i, 'wave')\n",
    "\n",
    "#bin the counts up for visualization purposes\n",
    "bin_num_comb=3\n",
    "for i in combined_specs:\n",
    "    group_width(i, bin_num_comb)\n",
    "\n",
    "#setup the combined arm labels for plotting\n",
    "arm_label_comb = ['three obsIDs +1/-1 combined heg','three obsIDs +1/-1 combined meg']\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "\n",
    "#plot the original (confused) HEG and MEG spectra in red\n",
    "plot(\"data\", 1, \"data\", 2, color='red',label=['confused','confused'], \n",
    "     yerrorbars=False, linestyle='-', marker=None)\n",
    "\n",
    "#overplot the new 'cleaned' HEG and MEG spectra in blue\n",
    "plot(\"data\", 3, \"data\", 4, color='blue',label=['cleaned','cleaned'],\n",
    "     overplot=True, yerrorbars=False, linestyle='-', marker=None)\n",
    "\n",
    "# set the same x-limits for all panels:\n",
    "axes = plt.gcf().axes\n",
    "for ax, arm in zip(axes,arm_label_comb):\n",
    "    ax.set_xlim(0,20)\n",
    "    ax.set_title(arm)\n",
    "\n",
    "#label the figure with color\n",
    "fig = plt.gcf()\n",
    "fig.text(0.30, 0.96, \"Confused\",  ha='left',  va='center', color='red',  fontsize=16)\n",
    "fig.text(0.425, .96, \"vs\",    va='center', color='black',  fontsize=16)\n",
    "fig.text(0.565, .96, \"Cleaned\", ha='right', va='center', color='blue', fontsize=16)\n",
    "plt.draw()\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "10a410db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "arm_label_comb_arf = ['three ObsIDs +1/-1 combined heg response',\n",
    "                      'three ObsIDs +1/-1 combined meg response']\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "#original ARFs\n",
    "plot(\"arf\", 1, \"arf\", 2, label=['confused','confused'], color='red')\n",
    "#cleaned ARFs\n",
    "plot(\"arf\", 3, \"arf\", 4, label=['cleaned','cleaned'],color='blue', overplot=True)\n",
    "\n",
    "axes = plt.gcf().axes\n",
    "for ax, arm in zip(axes,arm_label_comb_arf):\n",
    "    ax.set_xlim(0, 20)\n",
    "    ax.set_title(arm)\n",
    "\n",
    "plt.subplots_adjust(left=0, hspace=0.5, wspace=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73c0cf2d",
   "metadata": {},
   "source": [
    "As exposure time is increased with multiple ObsIDs, more emission lines are visible for COUP 394. Also note how the **combined** response does not go to zero because confusion does not occur at the same spot in all ObsIDs due to roll angle variations and source variability. Multiple observations can be used to mitigate confusion in crowded regions.This comparison of the original (confused) data with the cleaned data demonstrate the necessity to account for confusion from other sources in the field of view.  \n",
    "\n",
    "This also demonstrates how cleaning spectra takes away signal, which includes real data, too. In the MEG there is significant emission in the (real) Ne X emission line at 12.14 Å. However, in one of the observations a large region of the arm is potentially confused as thus filtered out (see the lower panel in the ARF plots, where the \"cleaned\" ARF is significantly below the \"confused\" ARF below 15.7 Å). This confusion is relevant for large ranges of that spectrum, in particular in regions where the source is weak. However, at 12.14 Å the source is so strong that is outshines any confusion, yet the real counts are also removed when the entire region is masked as \"potentially confused\" by crisscross. In that sense, crisscross is desined to be conservative and to mask all regions with potential confusion, but it is possible that this also removes counts in areas where the source is so bright that the relative contribution of the confusion is not significant."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96d4fb84",
   "metadata": {},
   "source": [
    "For questions, comments or suggestions about crisscross and its functionality, please contact [the CXC helpdesk](https://cxc.harvard.edu/help/) or through email at cxchelp@cfa.harvard.edu."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
